Syenira_Sheila_AnalisisSentimenIKN_SVM+QE.ipynb

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      "provenance": [],
      "toc_visible": true,
      "mount_file_id": "1i_Mmvvfd3Z7yhVf-K4wcQbFOWIyOFoK2",
      "authorship_tag": "ABX9TyNjgOut4k/8BqUmp3Etfhgf",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/syenirasheila/Sentiment-Analysis-IKN-Using-SVM-QE/blob/main/Syenira_Sheila_AnalisisSentimenIKN_SVM%2BQE.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# PENGUMPULAN DATA"
      ],
      "metadata": {
        "id": "KrPs2zgMNXQx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "pip install PySastrawi"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_fw9z50bNctn",
        "outputId": "ec27b688-ccf4-4253-f64a-27ce83d4be1c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: PySastrawi in /usr/local/lib/python3.8/dist-packages (1.2.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import joblib\n",
        "import pickle\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "from sklearn import model_selection\n",
        "from sklearn.metrics import classification_report\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn import datasets\n",
        "from sklearn.feature_extraction.text import CountVectorizer\n",
        "from sklearn.feature_extraction.text import TfidfTransformer\n",
        "from sklearn.pipeline import Pipeline\n",
        "from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score\n",
        "from sklearn.preprocessing import LabelEncoder\n",
        "from sklearn.svm import SVC\n",
        "from sklearn.model_selection import GridSearchCV\n",
        "from sklearn.feature_extraction.text import TfidfVectorizer\n",
        "from sklearn import svm\n",
        "\n",
        "\n",
        "import nltk\n",
        "import string\n",
        "import re\n",
        "from sklearn.metrics.pairwise import cosine_similarity\n",
        "from nltk.util import ngrams\n",
        "\n",
        "\n",
        "from Sastrawi.Stemmer.StemmerFactory import StemmerFactory"
      ],
      "metadata": {
        "id": "7UMCF95iNsck"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Koneksi ke Google Drive\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rNNhyNyQN2TO",
        "outputId": "b0fd517b-2f41-4096-fe14-0f07050479bd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Read the dataset\n",
        "df = pd.read_excel('/content/drive/MyDrive/Machine Learning 117/Analisis Sentimen IKN/Dataset/Sentimen Pengguna Twitter Pada Topik IKN.xlsx')\n",
        "df['Tweet']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mCZXShf9PfFx",
        "outputId": "814cf744-dead-4864-8fd0-c858b2d86875"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0       b'RT @AlshaibaShihab: Indonesia ditangan Presi...\n",
              "1       b'@PrathumRyan @pranjaya_baguz @MightyWar3 Bus...\n",
              "2       b'RT @Usuludin321: Bener juga yah kenapa sih m...\n",
              "3       b'RT @msaid_didu: Pddk 200.000 yg sebagian bes...\n",
              "4       b'RT @HendryanaLubis: @s1lverpegasus Dia pasti...\n",
              "                              ...                        \n",
              "2172    b'Progres IKN Pada Tahap Awal,Pembiayaan Masih...\n",
              "2173    b'APLN Garap Kawasan Hunian Super Premium Deka...\n",
              "2174    b'RT @HukumDan: Wuiih. Serius ini kek nya pind...\n",
              "2175    b'RT @LaNyallaAcademy: APA URGENSINYA SAMPAI H...\n",
              "2176    b'Masyarakat Kalimantan Timur Dukung Pembangun...\n",
              "Name: Tweet, Length: 2177, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "a6jVic7RRFE4",
        "outputId": "74d9f138-8b54-4592-98ed-a6d7634cbccb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "UFbzhEekROsa",
        "outputId": "e040ee62-f033-486b-c2a5-de5c463f5e3b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         No. Sentimen                                              Tweet\n",
              "0        1.0  Positif  b'RT @AlshaibaShihab: Indonesia ditangan Presi...\n",
              "1        2.0  Negatif  b'@PrathumRyan @pranjaya_baguz @MightyWar3 Bus...\n",
              "2        3.0  Negatif  b'RT @Usuludin321: Bener juga yah kenapa sih m...\n",
              "3        4.0  Negatif  b'RT @msaid_didu: Pddk 200.000 yg sebagian bes...\n",
              "4        5.0  Negatif  b'RT @HendryanaLubis: @s1lverpegasus Dia pasti...\n",
              "...      ...      ...                                                ...\n",
              "2172  2173.0  Positif  b'Progres IKN Pada Tahap Awal,Pembiayaan Masih...\n",
              "2173  2174.0  Positif  b'APLN Garap Kawasan Hunian Super Premium Deka...\n",
              "2174  2175.0  Negatif  b'RT @HukumDan: Wuiih. Serius ini kek nya pind...\n",
              "2175  2176.0  Negatif  b'RT @LaNyallaAcademy: APA URGENSINYA SAMPAI H...\n",
              "2176  2177.0  Positif  b'Masyarakat Kalimantan Timur Dukung Pembangun...\n",
              "\n",
              "[2177 rows x 3 columns]"
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>No.</th>\n",
              "      <th>Sentimen</th>\n",
              "      <th>Tweet</th>\n",
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              "      <th>0</th>\n",
              "      <td>1.0</td>\n",
              "      <td>Positif</td>\n",
              "      <td>b'RT @AlshaibaShihab: Indonesia ditangan Presi...</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2.0</td>\n",
              "      <td>Negatif</td>\n",
              "      <td>b'@PrathumRyan @pranjaya_baguz @MightyWar3 Bus...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3.0</td>\n",
              "      <td>Negatif</td>\n",
              "      <td>b'RT @Usuludin321: Bener juga yah kenapa sih m...</td>\n",
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              "      <th>3</th>\n",
              "      <td>4.0</td>\n",
              "      <td>Negatif</td>\n",
              "      <td>b'RT @msaid_didu: Pddk 200.000 yg sebagian bes...</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5.0</td>\n",
              "      <td>Negatif</td>\n",
              "      <td>b'RT @HendryanaLubis: @s1lverpegasus Dia pasti...</td>\n",
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              "      <th>2172</th>\n",
              "      <td>2173.0</td>\n",
              "      <td>Positif</td>\n",
              "      <td>b'Progres IKN Pada Tahap Awal,Pembiayaan Masih...</td>\n",
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              "    <tr>\n",
              "      <th>2173</th>\n",
              "      <td>2174.0</td>\n",
              "      <td>Positif</td>\n",
              "      <td>b'APLN Garap Kawasan Hunian Super Premium Deka...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2174</th>\n",
              "      <td>2175.0</td>\n",
              "      <td>Negatif</td>\n",
              "      <td>b'RT @HukumDan: Wuiih. Serius ini kek nya pind...</td>\n",
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              "    <tr>\n",
              "      <th>2175</th>\n",
              "      <td>2176.0</td>\n",
              "      <td>Negatif</td>\n",
              "      <td>b'RT @LaNyallaAcademy: APA URGENSINYA SAMPAI H...</td>\n",
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              "    <tr>\n",
              "      <th>2176</th>\n",
              "      <td>2177.0</td>\n",
              "      <td>Positif</td>\n",
              "      <td>b'Masyarakat Kalimantan Timur Dukung Pembangun...</td>\n",
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          },
          "metadata": {},
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Visualisasi Data\n",
        "plt.hist(df.Sentimen)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        },
        "id": "-itg-KMgRSZ8",
        "outputId": "227a5b7e-8ce4-40b0-a5a7-f7ca10704fe4"
      },
      "execution_count": null,
      "outputs": [
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([1451.,    0.,    0.,    0.,    0.,    0.,    0.,    0.,    0.,\n",
              "         726.]),\n",
              " array([0. , 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1. ]),\n",
              " <a list of 10 Patch objects>)"
            ]
          },
          "metadata": {},
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# PRE-PROCESSING TEXT"
      ],
      "metadata": {
        "id": "0Z9bfri2WN_2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Cleansing Data\n",
        "def cleansing(text):\n",
        "    #Menghilangkan tanda kurung\n",
        "    text = re.sub('\\[.*?\\]', '', text)\n",
        "    #Menghilangkan Tanda Baca\n",
        "    text = re.sub('[%s]' % re.escape(string.punctuation), '', text)\n",
        "    #Menghilangkan Special Karakter\n",
        "    text = re.sub('\\w*\\d\\w*', '', text)\n",
        "    #Menghilangkan Single Character\n",
        "    text = re.sub('\\s+[a-zA-Z]\\s+', '', text)\n",
        "    #Menghilangkan Link\n",
        "    text = re.sub(r\"http\\S+\", \"\", text, flags=re.MULTILINE)\n",
        "    #Menghilangkan Hashtag\n",
        "    text = re.sub(r'\\B#\\S+','', text)\n",
        "    #Mengganti Multiple Spaces ke Single Spaces\n",
        "    text = re.sub(r'\\s+', ' ', text, flags=re.I)\n",
        "    #Menghilangkan Spaces di awal\n",
        "    text = text.strip()\n",
        "    return text\n",
        "df['CLEANSING']= df['Tweet'].apply(lambda x: cleansing(x))"
      ],
      "metadata": {
        "id": "nt0XXTqrWUPd"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "eBXqXt6QWbjk",
        "outputId": "f36bfa1c-b0c3-4a1c-a82b-0e93d97dff00"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   No. Sentimen                                              Tweet  \\\n",
              "0  1.0  Positif  b'RT @AlshaibaShihab: Indonesia ditangan Presi...   \n",
              "1  2.0  Negatif  b'@PrathumRyan @pranjaya_baguz @MightyWar3 Bus...   \n",
              "2  3.0  Negatif  b'RT @Usuludin321: Bener juga yah kenapa sih m...   \n",
              "3  4.0  Negatif  b'RT @msaid_didu: Pddk 200.000 yg sebagian bes...   \n",
              "4  5.0  Negatif  b'RT @HendryanaLubis: @s1lverpegasus Dia pasti...   \n",
              "\n",
              "                                           CLEANSING  \n",
              "0  bRT AlshaibaShihab Indonesia ditangan Presiden...  \n",
              "1  bPrathumRyan pranjayabaguz Buset Miliar USD ka...  \n",
              "2  bRT Bener juga yah kenapa sih maksain bangun I...  \n",
              "3  bRT msaiddidu Pddk yg sebagian besar adalah AS...  \n",
              "4  bRT HendryanaLubis Dia pasti mendukung sapa yg...  "
            ],
            "text/html": [
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              "  <div id=\"df-862b694b-995b-49ff-a3a5-ff32531fe1f7\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "      <th>No.</th>\n",
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              "      <th>1</th>\n",
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              "      <td>Negatif</td>\n",
              "      <td>b'@PrathumRyan @pranjaya_baguz @MightyWar3 Bus...</td>\n",
              "      <td>bPrathumRyan pranjayabaguz Buset Miliar USD ka...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3.0</td>\n",
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              "      <td>bRT Bener juga yah kenapa sih maksain bangun I...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4.0</td>\n",
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              "      <td>bRT msaiddidu Pddk yg sebagian besar adalah AS...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5.0</td>\n",
              "      <td>Negatif</td>\n",
              "      <td>b'RT @HendryanaLubis: @s1lverpegasus Dia pasti...</td>\n",
              "      <td>bRT HendryanaLubis Dia pasti mendukung sapa yg...</td>\n",
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              "          document.querySelector('#df-862b694b-995b-49ff-a3a5-ff32531fe1f7 button.colab-df-convert');\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "          const element = document.querySelector('#df-862b694b-995b-49ff-a3a5-ff32531fe1f7');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.to_excel(\"/content/drive/MyDrive/Machine Learning 117/Analisis Sentimen IKN/Hasil QE/Cleansing.xlsx\")"
      ],
      "metadata": {
        "id": "nJvW4umQWfXA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#CaseFolding\n",
        "def case_folding(text):\n",
        "    text = text.lower()\n",
        "    return text\n",
        "df['CASEFOLDING']= df['CLEANSING'].apply(lambda x: case_folding(x))\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 337
        },
        "id": "MKYHwFZHWtFy",
        "outputId": "61440ed4-4659-4097-ad90-d60860e8e14a"
      },
      "execution_count": null,
      "outputs": [
        {
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              "   No. Sentimen                                              Tweet  \\\n",
              "0  1.0  Positif  b'RT @AlshaibaShihab: Indonesia ditangan Presi...   \n",
              "1  2.0  Negatif  b'@PrathumRyan @pranjaya_baguz @MightyWar3 Bus...   \n",
              "2  3.0  Negatif  b'RT @Usuludin321: Bener juga yah kenapa sih m...   \n",
              "3  4.0  Negatif  b'RT @msaid_didu: Pddk 200.000 yg sebagian bes...   \n",
              "4  5.0  Negatif  b'RT @HendryanaLubis: @s1lverpegasus Dia pasti...   \n",
              "\n",
              "                                           CLEANSING  \\\n",
              "0  bRT AlshaibaShihab Indonesia ditangan Presiden...   \n",
              "1  bPrathumRyan pranjayabaguz Buset Miliar USD ka...   \n",
              "2  bRT Bener juga yah kenapa sih maksain bangun I...   \n",
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              "                                         CASEFOLDING  \n",
              "0  brt alshaibashihab indonesia ditangan presiden...  \n",
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              "                                                     [key], {});\n",
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              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "         No. Sentimen                                              Tweet  \\\n",
              "0        1.0  Positif  b'RT @AlshaibaShihab: Indonesia ditangan Presi...   \n",
              "1        2.0  Negatif  b'@PrathumRyan @pranjaya_baguz @MightyWar3 Bus...   \n",
              "2        3.0  Negatif  b'RT @Usuludin321: Bener juga yah kenapa sih m...   \n",
              "3        4.0  Negatif  b'RT @msaid_didu: Pddk 200.000 yg sebagian bes...   \n",
              "4        5.0  Negatif  b'RT @HendryanaLubis: @s1lverpegasus Dia pasti...   \n",
              "...      ...      ...                                                ...   \n",
              "2172  2173.0  Positif  b'Progres IKN Pada Tahap Awal,Pembiayaan Masih...   \n",
              "2173  2174.0  Positif  b'APLN Garap Kawasan Hunian Super Premium Deka...   \n",
              "2174  2175.0  Negatif  b'RT @HukumDan: Wuiih. Serius ini kek nya pind...   \n",
              "2175  2176.0  Negatif  b'RT @LaNyallaAcademy: APA URGENSINYA SAMPAI H...   \n",
              "2176  2177.0  Positif  b'Masyarakat Kalimantan Timur Dukung Pembangun...   \n",
              "\n",
              "                                              CLEANSING  \\\n",
              "0     bRT AlshaibaShihab Indonesia ditangan Presiden...   \n",
              "1     bPrathumRyan pranjayabaguz Buset Miliar USD ka...   \n",
              "2     bRT Bener juga yah kenapa sih maksain bangun I...   \n",
              "3     bRT msaiddidu Pddk yg sebagian besar adalah AS...   \n",
              "4     bRT HendryanaLubis Dia pasti mendukung sapa yg...   \n",
              "...                                                 ...   \n",
              "2172  bProgres IKN Pada Tahap AwalPembiayaan Masih D...   \n",
              "2173  bAPLN Garap Kawasan Hunian Super Premium Dekat...   \n",
              "2174  bRT HukumDan Wuiih Serius ini kek nya pindah S...   \n",
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              "                                            CASEFOLDING  \n",
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              "1     bprathumryan pranjayabaguz buset miliar usd ka...  \n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "\n",
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              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-ddb4a62c-cc15-41e5-97cc-3acd54d2a0fe button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-ddb4a62c-cc15-41e5-97cc-3acd54d2a0fe');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Tokenizing\n",
        "#Tokenization\n",
        "def tokenization(text):\n",
        "    text = re.split('\\W+', text)\n",
        "    return text\n",
        "df['TOKENIZATION']= df['CASEFOLDING'].apply(lambda x: tokenization(x))\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 372
        },
        "id": "wjlBFNdxW0d8",
        "outputId": "f9d3da68-390f-4569-f0c5-faceda5e7e5a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   No. Sentimen                                              Tweet  \\\n",
              "0  1.0  Positif  b'RT @AlshaibaShihab: Indonesia ditangan Presi...   \n",
              "1  2.0  Negatif  b'@PrathumRyan @pranjaya_baguz @MightyWar3 Bus...   \n",
              "2  3.0  Negatif  b'RT @Usuludin321: Bener juga yah kenapa sih m...   \n",
              "3  4.0  Negatif  b'RT @msaid_didu: Pddk 200.000 yg sebagian bes...   \n",
              "4  5.0  Negatif  b'RT @HendryanaLubis: @s1lverpegasus Dia pasti...   \n",
              "\n",
              "                                           CLEANSING  \\\n",
              "0  bRT AlshaibaShihab Indonesia ditangan Presiden...   \n",
              "1  bPrathumRyan pranjayabaguz Buset Miliar USD ka...   \n",
              "2  bRT Bener juga yah kenapa sih maksain bangun I...   \n",
              "3  bRT msaiddidu Pddk yg sebagian besar adalah AS...   \n",
              "4  bRT HendryanaLubis Dia pasti mendukung sapa yg...   \n",
              "\n",
              "                                         CASEFOLDING  \\\n",
              "0  brt alshaibashihab indonesia ditangan presiden...   \n",
              "1  bprathumryan pranjayabaguz buset miliar usd ka...   \n",
              "2  brt bener juga yah kenapa sih maksain bangun i...   \n",
              "3  brt msaiddidu pddk yg sebagian besar adalah as...   \n",
              "4  brt hendryanalubis dia pasti mendukung sapa yg...   \n",
              "\n",
              "                                        TOKENIZATION  \n",
              "0  [brt, alshaibashihab, indonesia, ditangan, pre...  \n",
              "1  [bprathumryan, pranjayabaguz, buset, miliar, u...  \n",
              "2  [brt, bener, juga, yah, kenapa, sih, maksain, ...  \n",
              "3  [brt, msaiddidu, pddk, yg, sebagian, besar, ad...  \n",
              "4  [brt, hendryanalubis, dia, pasti, mendukung, s...  "
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>No.</th>\n",
              "      <th>Sentimen</th>\n",
              "      <th>Tweet</th>\n",
              "      <th>CLEANSING</th>\n",
              "      <th>CASEFOLDING</th>\n",
              "      <th>TOKENIZATION</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1.0</td>\n",
              "      <td>Positif</td>\n",
              "      <td>b'RT @AlshaibaShihab: Indonesia ditangan Presi...</td>\n",
              "      <td>bRT AlshaibaShihab Indonesia ditangan Presiden...</td>\n",
              "      <td>brt alshaibashihab indonesia ditangan presiden...</td>\n",
              "      <td>[brt, alshaibashihab, indonesia, ditangan, pre...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2.0</td>\n",
              "      <td>Negatif</td>\n",
              "      <td>b'@PrathumRyan @pranjaya_baguz @MightyWar3 Bus...</td>\n",
              "      <td>bPrathumRyan pranjayabaguz Buset Miliar USD ka...</td>\n",
              "      <td>bprathumryan pranjayabaguz buset miliar usd ka...</td>\n",
              "      <td>[bprathumryan, pranjayabaguz, buset, miliar, u...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3.0</td>\n",
              "      <td>Negatif</td>\n",
              "      <td>b'RT @Usuludin321: Bener juga yah kenapa sih m...</td>\n",
              "      <td>bRT Bener juga yah kenapa sih maksain bangun I...</td>\n",
              "      <td>brt bener juga yah kenapa sih maksain bangun i...</td>\n",
              "      <td>[brt, bener, juga, yah, kenapa, sih, maksain, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4.0</td>\n",
              "      <td>Negatif</td>\n",
              "      <td>b'RT @msaid_didu: Pddk 200.000 yg sebagian bes...</td>\n",
              "      <td>bRT msaiddidu Pddk yg sebagian besar adalah AS...</td>\n",
              "      <td>brt msaiddidu pddk yg sebagian besar adalah as...</td>\n",
              "      <td>[brt, msaiddidu, pddk, yg, sebagian, besar, ad...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5.0</td>\n",
              "      <td>Negatif</td>\n",
              "      <td>b'RT @HendryanaLubis: @s1lverpegasus Dia pasti...</td>\n",
              "      <td>bRT HendryanaLubis Dia pasti mendukung sapa yg...</td>\n",
              "      <td>brt hendryanalubis dia pasti mendukung sapa yg...</td>\n",
              "      <td>[brt, hendryanalubis, dia, pasti, mendukung, s...</td>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-9cd11ac3-cadf-42f3-91ef-2106d9cf43d5')\"\n",
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              "\n",
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              "          const element = document.querySelector('#df-9cd11ac3-cadf-42f3-91ef-2106d9cf43d5');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# read txt stopword using pandas\n",
        "txt_stopword = pd.read_excel(\"/content/drive/MyDrive/Machine Learning 117/Analisis Sentimen IKN/Kamus/kamus_stopword.xlsx\", names= [\"stopwords\"], header = None)\n",
        "\n",
        "# convert stopword string to list & append additional stopword\n",
        "list_stopwords = txt_stopword['stopwords'].values.tolist()\n",
        "\n",
        "# ---------------------------------------------------------------------------------------\n",
        "\n",
        "# convert list to dictionary\n",
        "list_stopwords = set(list_stopwords)\n",
        "\n",
        "\n",
        "#remove stopword pada list token\n",
        "def stopwords_removal(words):\n",
        "    return [word for word in words if word not in list_stopwords]\n",
        "\n",
        "df['STOP REMOVAL'] = df['TOKENIZATION'].apply(stopwords_removal)\n",
        "\n",
        "\n",
        "print(df['STOP REMOVAL'].head())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "m2U3BAexW5AK",
        "outputId": "6bcde604-45f7-483d-e231-21fe60de4b3d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0    [brt, alshaibashihab, indonesia, ditangan, pre...\n",
            "1    [bprathumryan, pranjayabaguz, buset, miliar, u...\n",
            "2         [brt, bener, yah, sih, maksain, bangun, ikn]\n",
            "3    [brt, msaiddidu, pddk, yg, asn, yg, gajinya, s...\n",
            "4    [brt, hendryanalubis, pasti, mendukung, sapa, ...\n",
            "Name: STOP REMOVAL, dtype: object\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.to_excel(\"/content/drive/MyDrive/Machine Learning 117/Analisis Sentimen IKN/Hasil QE/StopwordRemoval.xlsx\")"
      ],
      "metadata": {
        "id": "7Ka_Ypi1XDzl"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#StopwordRemoval\n",
        "final = pd.DataFrame(df, columns= ['Sentimen', 'STOP REMOVAL'])\n",
        "final"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "ti6PwHEYXMBH",
        "outputId": "434d7ee9-62fc-44a1-fcef-fd14bd3b4962"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Sentimen                                       STOP REMOVAL\n",
              "0     Positif  [brt, alshaibashihab, indonesia, ditangan, pre...\n",
              "1     Negatif  [bprathumryan, pranjayabaguz, buset, miliar, u...\n",
              "2     Negatif       [brt, bener, yah, sih, maksain, bangun, ikn]\n",
              "3     Negatif  [brt, msaiddidu, pddk, yg, asn, yg, gajinya, s...\n",
              "4     Negatif  [brt, hendryanalubis, pasti, mendukung, sapa, ...\n",
              "...       ...                                                ...\n",
              "2172  Positif  [bprogres, ikn, tahap, awalpembiayaan, masih, ...\n",
              "2173  Positif  [bapln, garap, kawasan, hunian, super, premium...\n",
              "2174  Negatif  [brt, hukumdan, wuiih, serius, kek, nya, pinda...\n",
              "2175  Negatif  [brt, lanyallaacademy, urgensinya, harus, meng...\n",
              "2176  Positif  [bmasyarakat, kalimantan, timur, dukung, pemba...\n",
              "\n",
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              "      <th>2173</th>\n",
              "      <td>Positif</td>\n",
              "      <td>[bapln, garap, kawasan, hunian, super, premium...</td>\n",
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              "    <tr>\n",
              "      <th>2174</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[brt, hukumdan, wuiih, serius, kek, nya, pinda...</td>\n",
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              "    <tr>\n",
              "      <th>2175</th>\n",
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              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-be6d8b19-f176-4ad7-85bc-85b696255339 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-be6d8b19-f176-4ad7-85bc-85b696255339');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install swifter"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "MrNMWqfQXPIT",
        "outputId": "90c2148a-8bc1-4ef3-c8ff-80cc240ad8ce"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting swifter\n",
            "  Downloading swifter-1.3.4.tar.gz (830 kB)\n",
            "\u001b[K     |████████████████████████████████| 830 kB 7.1 MB/s \n",
            "\u001b[?25hRequirement already satisfied: pandas>=1.0.0 in /usr/local/lib/python3.8/dist-packages (from swifter) (1.3.5)\n",
            "Collecting psutil>=5.6.6\n",
            "  Downloading psutil-5.9.4-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (280 kB)\n",
            "\u001b[K     |████████████████████████████████| 280 kB 50.8 MB/s \n",
            "\u001b[?25hRequirement already satisfied: dask[dataframe]>=2.10.0 in /usr/local/lib/python3.8/dist-packages (from swifter) (2022.2.1)\n",
            "Requirement already satisfied: tqdm>=4.33.0 in /usr/local/lib/python3.8/dist-packages (from swifter) (4.64.1)\n",
            "Requirement already satisfied: ipywidgets>=7.0.0 in /usr/local/lib/python3.8/dist-packages (from swifter) (7.7.1)\n",
            "Requirement already satisfied: cloudpickle>=0.2.2 in /usr/local/lib/python3.8/dist-packages (from swifter) (1.5.0)\n",
            "Requirement already satisfied: parso>0.4.0 in /usr/local/lib/python3.8/dist-packages (from swifter) (0.8.3)\n",
            "Requirement already satisfied: bleach>=3.1.1 in /usr/local/lib/python3.8/dist-packages (from swifter) (5.0.1)\n",
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            "Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask[dataframe]>=2.10.0->swifter) (0.12.0)\n",
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            "Requirement already satisfied: ipykernel>=4.5.1 in /usr/local/lib/python3.8/dist-packages (from ipywidgets>=7.0.0->swifter) (5.3.4)\n",
            "Requirement already satisfied: ipython>=4.0.0 in /usr/local/lib/python3.8/dist-packages (from ipywidgets>=7.0.0->swifter) (7.9.0)\n",
            "Requirement already satisfied: ipython-genutils~=0.2.0 in /usr/local/lib/python3.8/dist-packages (from ipywidgets>=7.0.0->swifter) (0.2.0)\n",
            "Requirement already satisfied: widgetsnbextension~=3.6.0 in /usr/local/lib/python3.8/dist-packages (from ipywidgets>=7.0.0->swifter) (3.6.1)\n",
            "Requirement already satisfied: jupyterlab-widgets>=1.0.0 in /usr/local/lib/python3.8/dist-packages (from ipywidgets>=7.0.0->swifter) (3.0.4)\n",
            "Requirement already satisfied: tornado>=4.2 in /usr/local/lib/python3.8/dist-packages (from ipykernel>=4.5.1->ipywidgets>=7.0.0->swifter) (6.0.4)\n",
            "Requirement already satisfied: jupyter-client in /usr/local/lib/python3.8/dist-packages (from ipykernel>=4.5.1->ipywidgets>=7.0.0->swifter) (6.1.12)\n",
            "Requirement already satisfied: pickleshare in /usr/local/lib/python3.8/dist-packages (from ipython>=4.0.0->ipywidgets>=7.0.0->swifter) (0.7.5)\n",
            "Requirement already satisfied: setuptools>=18.5 in /usr/local/lib/python3.8/dist-packages (from ipython>=4.0.0->ipywidgets>=7.0.0->swifter) (57.4.0)\n",
            "Requirement already satisfied: decorator in /usr/local/lib/python3.8/dist-packages (from ipython>=4.0.0->ipywidgets>=7.0.0->swifter) (4.4.2)\n",
            "Requirement already satisfied: pexpect in /usr/local/lib/python3.8/dist-packages (from ipython>=4.0.0->ipywidgets>=7.0.0->swifter) (4.8.0)\n",
            "Collecting jedi>=0.10\n",
            "  Downloading jedi-0.18.2-py2.py3-none-any.whl (1.6 MB)\n",
            "\u001b[K     |████████████████████████████████| 1.6 MB 50.7 MB/s \n",
            "\u001b[?25hRequirement already satisfied: pygments in /usr/local/lib/python3.8/dist-packages (from ipython>=4.0.0->ipywidgets>=7.0.0->swifter) (2.6.1)\n",
            "Requirement already satisfied: prompt-toolkit<2.1.0,>=2.0.0 in /usr/local/lib/python3.8/dist-packages (from ipython>=4.0.0->ipywidgets>=7.0.0->swifter) (2.0.10)\n",
            "Requirement already satisfied: backcall in /usr/local/lib/python3.8/dist-packages (from ipython>=4.0.0->ipywidgets>=7.0.0->swifter) (0.2.0)\n",
            "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging>=20.0->dask[dataframe]>=2.10.0->swifter) (3.0.9)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas>=1.0.0->swifter) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas>=1.0.0->swifter) (2022.6)\n",
            "Requirement already satisfied: locket in /usr/local/lib/python3.8/dist-packages (from partd>=0.3.10->dask[dataframe]>=2.10.0->swifter) (1.0.0)\n",
            "Requirement already satisfied: wcwidth in /usr/local/lib/python3.8/dist-packages (from prompt-toolkit<2.1.0,>=2.0.0->ipython>=4.0.0->ipywidgets>=7.0.0->swifter) (0.2.5)\n",
            "Requirement already satisfied: notebook>=4.4.1 in /usr/local/lib/python3.8/dist-packages (from widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (5.7.16)\n",
            "Requirement already satisfied: Send2Trash in /usr/local/lib/python3.8/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (1.8.0)\n",
            "Requirement already satisfied: nbformat in /usr/local/lib/python3.8/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (5.7.0)\n",
            "Requirement already satisfied: prometheus-client in /usr/local/lib/python3.8/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (0.15.0)\n",
            "Requirement already satisfied: nbconvert<6.0 in /usr/local/lib/python3.8/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (5.6.1)\n",
            "Requirement already satisfied: pyzmq>=17 in /usr/local/lib/python3.8/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (23.2.1)\n",
            "Requirement already satisfied: jinja2<=3.0.0 in /usr/local/lib/python3.8/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (2.11.3)\n",
            "Requirement already satisfied: terminado>=0.8.1 in /usr/local/lib/python3.8/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (0.13.3)\n",
            "Requirement already satisfied: jupyter-core>=4.4.0 in /usr/local/lib/python3.8/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (5.1.0)\n",
            "Requirement already satisfied: MarkupSafe>=0.23 in /usr/local/lib/python3.8/dist-packages (from jinja2<=3.0.0->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (2.0.1)\n",
            "Requirement already satisfied: platformdirs>=2.5 in /usr/local/lib/python3.8/dist-packages (from jupyter-core>=4.4.0->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (2.6.0)\n",
            "Requirement already satisfied: pandocfilters>=1.4.1 in /usr/local/lib/python3.8/dist-packages (from nbconvert<6.0->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (1.5.0)\n",
            "Requirement already satisfied: testpath in /usr/local/lib/python3.8/dist-packages (from nbconvert<6.0->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (0.6.0)\n",
            "Requirement already satisfied: defusedxml in /usr/local/lib/python3.8/dist-packages (from nbconvert<6.0->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (0.7.1)\n",
            "Requirement already satisfied: mistune<2,>=0.8.1 in /usr/local/lib/python3.8/dist-packages (from nbconvert<6.0->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (0.8.4)\n",
            "Requirement already satisfied: entrypoints>=0.2.2 in /usr/local/lib/python3.8/dist-packages (from nbconvert<6.0->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (0.4)\n",
            "Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (4.3.3)\n",
            "Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (2.16.2)\n",
            "Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (0.19.2)\n",
            "Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (22.1.0)\n",
            "Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (5.10.1)\n",
            "Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (3.11.0)\n",
            "Requirement already satisfied: ptyprocess in /usr/local/lib/python3.8/dist-packages (from terminado>=0.8.1->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.0.0->swifter) (0.7.0)\n",
            "Building wheels for collected packages: swifter\n",
            "  Building wheel for swifter (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for swifter: filename=swifter-1.3.4-py3-none-any.whl size=16321 sha256=2485c87c726196658df04f438385349ae95f380488ccfe23733422367d8b2bb5\n",
            "  Stored in directory: /root/.cache/pip/wheels/08/66/b4/921e351e63d88696932279d6163e125727c9da70ed8ca38419\n",
            "Successfully built swifter\n",
            "Installing collected packages: jedi, psutil, swifter\n",
            "  Attempting uninstall: psutil\n",
            "    Found existing installation: psutil 5.4.8\n",
            "    Uninstalling psutil-5.4.8:\n",
            "      Successfully uninstalled psutil-5.4.8\n",
            "Successfully installed jedi-0.18.2 psutil-5.9.4 swifter-1.3.4\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "psutil"
                ]
              }
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Stemming\n",
        "import swifter\n",
        "# create stemmer\n",
        "factory = StemmerFactory()\n",
        "stemmer = factory.create_stemmer()\n",
        "\n",
        "# stemmed\n",
        "def stemmed_wrapper(term):\n",
        "    return stemmer.stem(term)\n",
        "\n",
        "term_dict = {}\n",
        "\n",
        "for document in final['STOP REMOVAL']:\n",
        "    for term in document:\n",
        "        if term not in term_dict:\n",
        "            term_dict[term] = ' '\n",
        "\n",
        "print(len(term_dict))\n",
        "print(\"------------------------\")\n",
        "\n",
        "for term in term_dict:\n",
        "    term_dict[term] = stemmed_wrapper(term)\n",
        "    print(term,\":\" ,term_dict[term])\n",
        "\n",
        "print(term_dict)\n",
        "print(\"------------------------\")\n",
        "\n",
        "\n",
        "# apply stemmed term to dataframe\n",
        "def get_stemmed_term(document):\n",
        "    return [term_dict[term] for term in document]\n",
        "\n",
        "final['STEMMING'] = final['STOP REMOVAL'].apply(get_stemmed_term)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yNA-jdJtXTwM",
        "outputId": "505134c6-21c9-4644-effb-76ac0e96736e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2425\n",
            "------------------------\n",
            "brt : brt\n",
            "alshaibashihab : alshaibashihab\n",
            "indonesia : indonesia\n",
            "ditangan : tang\n",
            "presiden : presiden\n",
            "jokowi : jokowi\n",
            "bendungan : bendung\n",
            "ruas : ruas\n",
            "jalan : jalan\n",
            "bandara : bandara\n",
            "barunsirkuit : barunsirkuit\n",
            "mandalikankereta : mandalikankereta\n",
            "api : api\n",
            "bprathumryan : bprathumryan\n",
            "pranjayabaguz : pranjayabaguz\n",
            "buset : buset\n",
            "miliar : miliar\n",
            "usd : usd\n",
            "kalahin : kalahin\n",
            "anggaran : anggar\n",
            "militer : militer\n",
            "bener : bener\n",
            "yah : yah\n",
            "sih : sih\n",
            "maksain : maksain\n",
            "bangun : bangun\n",
            "ikn : ikn\n",
            "msaiddidu : msaiddidu\n",
            "pddk : pddk\n",
            "yg : yg\n",
            "asn : asn\n",
            "gajinya : gaji\n",
            "sdh : sdh\n",
            "habis : habis\n",
            "utk : utk\n",
            "cicilan : cicil\n",
            "rumah : rumah\n",
            "kendaraan : kendara\n",
            "biaya : biaya\n",
            "anak : anak\n",
            "sekolah : sekolah\n",
            "shg : shg\n",
            "hendryanalubis : hendryanalubis\n",
            "pasti : pasti\n",
            "mendukung : dukung\n",
            "sapa : sapa\n",
            "bisa : bisa\n",
            "lanjutkan : lanjut\n",
            "orang : orang\n",
            "berani : berani\n",
            "gk : gk\n",
            "kalo : kalo\n",
            "pindah : pindah\n",
            "kalimnatannnburuan : kalimnatannnburuan\n",
            "bpemerintah : bpemerintah\n",
            "susun : susun\n",
            "rencana : rencana\n",
            "pengembangan : kembang\n",
            "infrastruktur : infrastruktur\n",
            "hunian : huni\n",
            "penting : penting\n",
            "entaskan : entas\n",
            "kemiskinan : miskin\n",
            "mas : mas\n",
            "joko : joko\n",
            "menggenaskan : menggenaskan\n",
            "masse : masse\n",
            "menyusun : susun\n",
            "penduduk : duduk\n",
            "kota : kota\n",
            "nusantara : nusantara\n",
            "bzackyramadhani : bzackyramadhani\n",
            "nanya : nanya\n",
            "fungsi : fungsi\n",
            "biar : biar\n",
            "ku : ku\n",
            "kasih : kasih\n",
            "tau : tau\n",
            "ya : ya\n",
            "salah : salah\n",
            "upaya : upaya\n",
            "keuangannewsid : keuangannewsid\n",
            "buntu : buntu\n",
            "dampak : dampak\n",
            "positifbagi : positifbagi\n",
            "kemajuan : maju\n",
            "bangsa : bangsa\n",
            "gak : gak\n",
            "demo : demo\n",
            "bohirnya : bohirnya\n",
            "memikirkan : pikir\n",
            "tinggal : tinggal\n",
            "ibukota : ibukota\n",
            "representasi : representasi\n",
            "guzelamare : guzelamare\n",
            "iyalah : iya\n",
            "twitter : twitter\n",
            "mah : mah\n",
            "kliatan : kliatan\n",
            "visi : visi\n",
            "misi : misi\n",
            "nya : nya\n",
            "investor : investor\n",
            "blm : blm\n",
            "mau : mau\n",
            "bp : bp\n",
            "sbg : sbg\n",
            "markreting : markreting\n",
            "berkelas : kelas\n",
            "internasional : internasional\n",
            "bcnnindonesia : bcnnindonesia\n",
            "ngebet : ngebet\n",
            "pejabat : jabat\n",
            "silahkan : silah\n",
            "aja : aja\n",
            "pakai : pakai\n",
            "uang : uang\n",
            "hasil : hasil\n",
            "korupsi : korupsi\n",
            "ditindak : tindak\n",
            "serius : serius\n",
            "bmendukung : bmendukung\n",
            "mengawal : awal\n",
            "terus : terus\n",
            "pemindahan : pindah\n",
            "bergetarnusa : bergetarnusa\n",
            "maryshelparaiso : maryshelparaiso\n",
            "arek : arek\n",
            "jawa : jawa\n",
            "timur : timur\n",
            "dukung : dukung\n",
            "pembangunan : bangun\n",
            "kotaduniauntuksemua : kotaduniauntuksemua\n",
            "bikn : bikn\n",
            "berkonsep : konsep\n",
            "ramah : ramah\n",
            "bpembangunan : bpembangunan\n",
            "dilaksanakan : laksana\n",
            "bdukung : bdukung\n",
            "mpr : mpr\n",
            "ri : ri\n",
            "keluarkan : keluar\n",
            "ketetapan : tetap\n",
            "bberikut : bberikut\n",
            "manfaat : manfaat\n",
            "perekonomian : ekonomi\n",
            "positifuntuk : positifuntuk\n",
            "aceh : aceh\n",
            "hadir : hadir\n",
            "targetkan : target\n",
            "dihuni : huni\n",
            "bpresiden : bpresiden\n",
            "meluncurkan : luncur\n",
            "jagat : jagat\n",
            "metaverse : metaverse\n",
            "green : green\n",
            "bteguhsd : bteguhsd\n",
            "ih : ih\n",
            "ko : ko\n",
            "ngeyel : ngeyel\n",
            "bmsaiddidu : bmsaiddidu\n",
            "gimana : gimana\n",
            "ngitungnya : ngitungnya\n",
            "rb : rb\n",
            "warga : warga\n",
            "ngimpi : ngimpi\n",
            "kok : kok\n",
            "keterlaluan : terlalu\n",
            "ragilsemar : ragilsemar\n",
            "diawali : awal\n",
            "konsep : konsep\n",
            "pendanaan : dana\n",
            "menjadikan : jadi\n",
            "pemerintah : perintah\n",
            "penyewa : sewa\n",
            "ntentu : ntentu\n",
            "bbergetarnusa : bbergetarnusa\n",
            "membuka : buka\n",
            "lapangan : lapang\n",
            "kerja : kerja\n",
            "masyarakat : masyarakat\n",
            "kesejahteraan : sejahtera\n",
            "boposisicerdas : boposisicerdas\n",
            "baik : baik\n",
            "gubernur : gubernur\n",
            "fgelael : fgelael\n",
            "dibangunnya : bangun\n",
            "elemen : elemen\n",
            "membawa : bawa\n",
            "bdamri : bdamri\n",
            "hadirkan : hadir\n",
            "rute : rute\n",
            "balikpapanikn : balikpapanikn\n",
            "tarifnya : tarif\n",
            "rp : rp\n",
            "bmaryshelparaiso : bmaryshelparaiso\n",
            "saya : saya\n",
            "asli : asli\n",
            "untung : untung\n",
            "invest : invest\n",
            "ourlittleboyz : ourlittleboyz\n",
            "bfgelael : bfgelael\n",
            "dibangun : bangun\n",
            "irmansyahadhy : irmansyahadhy\n",
            "jualan : jual\n",
            "esemkaskrg : esemkaskrg\n",
            "iknnsebenarx : iknnsebenarx\n",
            "cebong : cebong\n",
            "kemarin : kemarin\n",
            "pilih : pilih\n",
            "makelar : makelar\n",
            "smart : smart\n",
            "city : city\n",
            "siap : siap\n",
            "bersaing : saing\n",
            "doktertifa : doktertifa\n",
            "badai : badai\n",
            "dunia : dunia\n",
            "gelap : gelap\n",
            "resesi : resesi\n",
            "dahsyat : dahsyat\n",
            "rawan : rawan\n",
            "pangan : pangan\n",
            "hebat : hebat\n",
            "nnkenapa : nnkenapa\n",
            "masih : masih\n",
            "ngotot : ngotot\n",
            "bsaudaraku : bsaudaraku\n",
            "sebangsa : bangsa\n",
            "setanah : tanah\n",
            "air : air\n",
            "kesadaran : sadar\n",
            "manusia : manusia\n",
            "waras : waras\n",
            "meningkatkan : tingkat\n",
            "ekonomi : ekonomi\n",
            "bengkulu : bengkulu\n",
            "mendorong : dorong\n",
            "yaniarsim : yaniarsim\n",
            "obral : obral\n",
            "investasi : investasi\n",
            "hgb : hgb\n",
            "thn : thn\n",
            "bebas : bebas\n",
            "pajak : pajak\n",
            "disc : disc\n",
            "nkini : nkini\n",
            "khusus : khusus\n",
            "danai : dana\n",
            "iknnkere : iknnkere\n",
            "bkeran : bkeran\n",
            "luncurkan : luncur\n",
            "nusantaranibukotanegaraniknnsemangatnusantara : nusantaranibukotanegaraniknnsemangatnusantara\n",
            "sasmojon : sasmojon\n",
            "oposisicerdas : oposisicerdas\n",
            "saking : saking\n",
            "nggak : nggak\n",
            "lakunya : laku\n",
            "iknnmending : iknnmending\n",
            "program : program\n",
            "transmigrasi : transmigrasi\n",
            "jaman : jaman\n",
            "kiyaimarufamin : kiyaimarufamin\n",
            "kesempatan : sempat\n",
            "mengajak : ajak\n",
            "dubai : dubai\n",
            "holding : holding\n",
            "menanamkan : tanam\n",
            "sektor : sektor\n",
            "dipikirkan : pikir\n",
            "kelas : kelas\n",
            "menengah : tengah\n",
            "bawag : bawag\n",
            "menjerit : jerit\n",
            "akibat : akibat\n",
            "byaniarsim : byaniarsim\n",
            "aniesbaswedan : aniesbaswedan\n",
            "gagal : gagal\n",
            "kayak : kayak\n",
            "dki : dki\n",
            "tidak : tidak\n",
            "teruskan : terus\n",
            "maju : maju\n",
            "bmaruf : bmaruf\n",
            "pusat : pusat\n",
            "industri : industri\n",
            "tangan : tangan\n",
            "ganjarpranowo : ganjarpranowo\n",
            "nti : nti\n",
            "landasan : landas\n",
            "dpt : dpt\n",
            "disempurnakan : sempurna\n",
            "bpaltiwest : bpaltiwest\n",
            "negeri : negeri\n",
            "pemilu : milu\n",
            "menang : menang\n",
            "bukan : bukan\n",
            "jagoannya : jago\n",
            "negara : negara\n",
            "bselama : bselama\n",
            "penguasa : kuasa\n",
            "berkuasa : kuasa\n",
            "seringkali : seringkali\n",
            "enggan : enggan\n",
            "menerima : terima\n",
            "masukan : masuk\n",
            "saran : saran\n",
            "nasihat : nasihat\n",
            "twiter : twiter\n",
            "untungikn : untungikn\n",
            "ja : ja\n",
            "dgn : dgn\n",
            "asemka : asemka\n",
            "bmembuka : bmembuka\n",
            "bindra : bindra\n",
            "karya : karya\n",
            "garap : garap\n",
            "proyek : proyek\n",
            "dasar : dasar\n",
            "wajah : wajah\n",
            "mata : mata\n",
            "ptppid : ptppid\n",
            "uppdate : uppdate\n",
            "balikpapan : balikpapan\n",
            "ptpp : ptpp\n",
            "menandatangani : menandatangani\n",
            "kontrak : kontrak\n",
            "pekerjaan : kerja\n",
            "eropa : eropa\n",
            "nangis : nang\n",
            "liat : liat\n",
            "batu : batu\n",
            "bara : bara\n",
            "dijadikan : jadi\n",
            "dinding : dinding\n",
            "pembatas : batas\n",
            "btxtdrpemerintah : btxtdrpemerintah\n",
            "dibanding : banding\n",
            "pendidikan : didik\n",
            "ingatlah : ingat\n",
            "menyetujui : tuju\n",
            "amp : amp\n",
            "mengesyahkan : syah\n",
            "nnjangan : nnjangan\n",
            "tenggelamkan : tenggelam\n",
            "udahbangun : udahbangun\n",
            "cepetannasn : cepetannasn\n",
            "cepetan : cepetan\n",
            "suruh : suruh\n",
            "pindahngw : pindahngw\n",
            "proyeksikan : proyeksi\n",
            "muncul : muncul\n",
            "bgeloraco : bgeloraco\n",
            "ayo : ayo\n",
            "apbn : apbn\n",
            "kereta : kereta\n",
            "cepat : cepat\n",
            "mobil : mobil\n",
            "listriknnga : listriknnga\n",
            "ribu : ribu\n",
            "presidennya : presiden\n",
            "yogaswarawahyu : yogaswarawahyu\n",
            "batalkan : batal\n",
            "sy : sy\n",
            "rakyat : rakyat\n",
            "ide : ide\n",
            "penjara : penjara\n",
            "bairkamiid : bairkamiid\n",
            "lama : lama\n",
            "jakarta : jakarta\n",
            "berkurang : kurang\n",
            "pindang : pindang\n",
            "bdetikcom : bdetikcom\n",
            "seramai : serama\n",
            "terkait : kait\n",
            "provinsi : provinsi\n",
            "kalimantan : kalimantan\n",
            "menjalin : jalin\n",
            "update : update\n",
            "progres : progres\n",
            "timurnnberikut : timurnnberikut\n",
            "kita : kita\n",
            "btheschloss : btheschloss\n",
            "santorinissun : santorinissun\n",
            "stefanantonio : stefanantonio\n",
            "outofthebay : outofthebay\n",
            "guoblokkknnikn : guoblokkknnikn\n",
            "kcic : kcic\n",
            "blampung : blampung\n",
            "percaya : percaya\n",
            "perubahan : ubah\n",
            "bmasyarakat : bmasyarakat\n",
            "lampung : lampung\n",
            "bpemindahan : bpemindahan\n",
            "sejarah : sejarah\n",
            "tersendiri : sendiri\n",
            "keuntungan : untung\n",
            "berkah : berkah\n",
            "peroleh : oleh\n",
            "perpindahan : pindah\n",
            "kebijakan : bijak\n",
            "btopansolawase : btopansolawase\n",
            "sirqieee : sirqieee\n",
            "mahfud : mahfud\n",
            "diuntungkansapa : diuntungkansapa\n",
            "dirugikan : rugi\n",
            "mayan : mayan\n",
            "dana : dana\n",
            "ubah : ubah\n",
            "uu : uu\n",
            "jkw : jkw\n",
            "pembagian : bagi\n",
            "sda : sda\n",
            "timpang : timpang\n",
            "ndak : ndak\n",
            "kekurangan : kurang\n",
            "tak : tak\n",
            "rela : rela\n",
            "uangnya : uang\n",
            "dipakai : pakai\n",
            "bayar : bayar\n",
            "utang : utang\n",
            "hukumdan : hukumdan\n",
            "bowoendarto : bowoendarto\n",
            "yaqutcqoumas : yaqutcqoumas\n",
            "yaqutqoumas : yaqutqoumas\n",
            "bodoh : bodoh\n",
            "kaya : kaya\n",
            "loe : loe\n",
            "bwapres : bwapres\n",
            "tawarkan : tawar\n",
            "petinggi : petinggi\n",
            "bfransiskusjurin : bfransiskusjurin\n",
            "durian : durian\n",
            "kompom : kompom\n",
            "amin : amin\n",
            "ajak : ajak\n",
            "berinvestasi : investasi\n",
            "bkadin : bkadin\n",
            "berharap : harap\n",
            "badan : badan\n",
            "otorita : otorita\n",
            "detail : detail\n",
            "paket : paket\n",
            "investasinarsjad : investasinarsjad\n",
            "rasjid : rasjid\n",
            "inklusifkolab : inklusifkolab\n",
            "arsjad : arsjad\n",
            "pengusaha : usaha\n",
            "global : global\n",
            "forum : forum\n",
            "november : november\n",
            "buka : buka\n",
            "lokal : lokal\n",
            "berpartisipasi : partisipasi\n",
            "papaloren : papaloren\n",
            "temen : temen\n",
            "sodara : sodara\n",
            "tante : tante\n",
            "ponakan : ponakan\n",
            "adek : adek\n",
            "mertus : mertus\n",
            "jetli : jetli\n",
            "bermanfaat : manfaat\n",
            "umkm : umkm\n",
            "mari : mari\n",
            "celoteh : celoteh\n",
            "bluar : bluar\n",
            "dukungan : dukung\n",
            "proses : proses\n",
            "berdampak : dampak\n",
            "positifdukung : positifdukung\n",
            "strategis : strategis\n",
            "memperkenalkan : kenal\n",
            "percepatan : cepat\n",
            "bseluruh : bseluruh\n",
            "jayalah : jaya\n",
            "indonesiaku : indonesia\n",
            "bkami : bkami\n",
            "berkomitmen : komitmen\n",
            "penuh : penuh\n",
            "menjaga : jaga\n",
            "kondusif : kondusif\n",
            "wilayah : wilayah\n",
            "kelancaran : lancar\n",
            "iknsejahterakanindonesia : iknsejahterakanindonesia\n",
            "iknpemerataanekonomi : iknpemerataanekonomi\n",
            "birhamnapermana : birhamnapermana\n",
            "kasi : kasi\n",
            "export : export\n",
            "layak : layak\n",
            "woy : woy\n",
            "merata : rata\n",
            "bwarga : bwarga\n",
            "ikntingkatkankesejahteraan : ikntingkatkankesejahteraan\n",
            "dukungiknnusantara : dukungiknnusantara\n",
            "bsurat : bsurat\n",
            "penunjukan : tunjuk\n",
            "penyedia : sedia\n",
            "barangjasa : barangjasa\n",
            "pelaksanaan : laksana\n",
            "manajemen : manajemen\n",
            "konstruksi : konstruksi\n",
            "induk : induk\n",
            "kegiatan : giat\n",
            "kadin : kadin\n",
            "nusantaranarsjad : nusantaranarsjad\n",
            "bpelaksanaan : bpelaksanaan\n",
            "pengadaan : ada\n",
            "barang : barang\n",
            "jasa : jasa\n",
            "dimana : mana\n",
            "pt : pt\n",
            "indra : indra\n",
            "persero : persero\n",
            "bjokowi : bjokowi\n",
            "nusantaranpresiden : nusantaranpresiden\n",
            "jokowinnaceh : jokowinnaceh\n",
            "teguhsd : teguhsd\n",
            "terwujud : wujud\n",
            "bgok : bgok\n",
            "ari : ari\n",
            "perusahaan : usaha\n",
            "berperan : peran\n",
            "meminimalisir : meminimalisir\n",
            "risiko : risiko\n",
            "mencapai : capai\n",
            "tujuan : tuju\n",
            "kami : kami\n",
            "memperhatikan : perhati\n",
            "mutu : mutu\n",
            "bangunan : bangun\n",
            "bsejalan : bsejalan\n",
            "pernyataan : nyata\n",
            "dirjen : dirjen\n",
            "cipta : cipta\n",
            "direktur : direktur\n",
            "utama : utama\n",
            "gok : gok\n",
            "joso : joso\n",
            "simamora : simamora\n",
            "bkapolres : bkapolres\n",
            "ppu : ppu\n",
            "sambut : sambut\n",
            "wakapolda : wakapolda\n",
            "kaltim : kaltim\n",
            "rangka : rangka\n",
            "tinjau : tinjau\n",
            "bkerennikn : bkerennikn\n",
            "perpresentasi : presentasi\n",
            "unggulnnaceh : unggulnnaceh\n",
            "bpantes : bpantes\n",
            "oligar : oligar\n",
            "panik : panik\n",
            "tanda : tanda\n",
            "buzzer : buzzer\n",
            "membabi : babi\n",
            "buta : buta\n",
            "pengiringan : iring\n",
            "narasi : narasi\n",
            "sesat : sesat\n",
            "nyanjk : nyanjk\n",
            "bkementerian : bkementerian\n",
            "perumahan : rumah\n",
            "pupr : pupr\n",
            "merancang : rancang\n",
            "bertujuan : tuju\n",
            "mengintegrasikan : integrasi\n",
            "mentransformasikan : transformasi\n",
            "lingkungannhanya : lingkungannhanya\n",
            "hijaunsisanya : hijaunsisanya\n",
            "korantempo : korantempo\n",
            "pdb : pdb\n",
            "nilainya : nilai\n",
            "arunariftan : arunariftan\n",
            "hnurwahid : hnurwahid\n",
            "gardagerilyagp : gardagerilyagp\n",
            "provokasi : provokasi\n",
            "org : org\n",
            "ga : ga\n",
            "sejalan : jalan\n",
            "mafia : mafia\n",
            "laksanakan : laksana\n",
            "beratahap : beratahap\n",
            "mengusung : usung\n",
            "future : future\n",
            "iknnkotaduniauntuksemua : iknnkotaduniauntuksemua\n",
            "bsiap : bsiap\n",
            "menanti : nanti\n",
            "tersohor : sohor\n",
            "btak : btak\n",
            "dipungkiri : dipungkiri\n",
            "kehadiran : hadir\n",
            "dorong : dorong\n",
            "boptimis : boptimis\n",
            "wujudkan : wujud\n",
            "berkunjung : kunjung\n",
            "kawasan : kawasan\n",
            "jalannya : jalan\n",
            "lahan : lahan\n",
            "persemaian : semai\n",
            "akses : akses\n",
            "bmemajukan : bmemajukan\n",
            "membangun : bangun\n",
            "bsemakin : bsemakin\n",
            "ramai : ramai\n",
            "byakin : byakin\n",
            "positifkotaduniauntuksemua : positifkotaduniauntuksemua\n",
            "antusias : antusias\n",
            "positifnkotaduniauntuksemua : positifnkotaduniauntuksemua\n",
            "bfuture : bfuture\n",
            "forest : forest\n",
            "peradaban : adab\n",
            "terpandang : pandang\n",
            "lingkungannkotaduniauntuksemua : lingkungannkotaduniauntuksemua\n",
            "unggulnkotaduniauntuksemua : unggulnkotaduniauntuksemua\n",
            "nasionalnkotaduniauntuksemua : nasionalnkotaduniauntuksemua\n",
            "zelensky : zelensky\n",
            "bilang : bilang\n",
            "udah : udah\n",
            "urus : urus\n",
            "mampu : mampu\n",
            "mw : mw\n",
            "negera : negera\n",
            "sdg : sdg\n",
            "konflik : konflik\n",
            "pla : pla\n",
            "terkatung : katung\n",
            "nyaiibubu : nyaiibubu\n",
            "klo : klo\n",
            "iknsaya : iknsaya\n",
            "yakin : yakin\n",
            "mayoritas : mayoritas\n",
            "jd : jd\n",
            "pengangguran : anggur\n",
            "job : job\n",
            "ongkosi : ongkos\n",
            "transport : transport\n",
            "fix : fix\n",
            "haram : haram\n",
            "hukumnya : hukum\n",
            "kadrun : kadrun\n",
            "hidup : hidup\n",
            "bnyaiibubu : bnyaiibubu\n",
            "ferlynorman : ferlynorman\n",
            "ramlirizal : ramlirizal\n",
            "bang : bang\n",
            "noam : noam\n",
            "chomsky : chomsky\n",
            "modern : modern\n",
            "state : state\n",
            "ankiiim : ankiiim\n",
            "prof : prof\n",
            "firman : firman\n",
            "noor : noor\n",
            "anies : anies\n",
            "kandidat : kandidat\n",
            "capres : capres\n",
            "lawan : lawan\n",
            "sm : sm\n",
            "proffirman : proffirman\n",
            "cuma : cuma\n",
            "elon : elon\n",
            "emoh : emoh\n",
            "krn : krn\n",
            "bengkak : bengkak\n",
            "bolak : bolak\n",
            "ditipu : tipu\n",
            "pasrah : pasrah\n",
            "beropa : opa\n",
            "dipaksa : paksa\n",
            "inves : inves\n",
            "wkwk : wkwk\n",
            "mending : mending\n",
            "ngibul : ngibul\n",
            "dululah : dululah\n",
            "baprilialin : baprilialin\n",
            "kpkri : kpkri\n",
            "hehhbegoitu : hehhbegoitu\n",
            "freeport : freeport\n",
            "gimanapertambangan : gimanapertambangan\n",
            "diluar : luar\n",
            "gimanaikn : gimanaikn\n",
            "hutan : hutan\n",
            "membengkak : bengkak\n",
            "triliunn : triliunn\n",
            "instruksi : instruksi\n",
            "sepi : sepi\n",
            "ragu : ragu\n",
            "nanam : nanam\n",
            "modal : modal\n",
            "bbersama : bbersama\n",
            "sukseskan : sukses\n",
            "bini : bini\n",
            "betul : betul\n",
            "merefleksikan : refleksi\n",
            "caracara : caracara\n",
            "bdengan : bdengan\n",
            "luas : luas\n",
            "lk : lk\n",
            "hektar : hektar\n",
            "mentawir : mentawir\n",
            "ditargetkan : target\n",
            "memproduksi : produksi\n",
            "bibit : bibit\n",
            "juta : juta\n",
            "bsobat : bsobat\n",
            "hijau : hijau\n",
            "semangat : semangat\n",
            "jumatnnsemangat : jumatnnsemangat\n",
            "tekad : tekad\n",
            "penghijauan : hijau\n",
            "jambi : jambi\n",
            "transformasi : transformasi\n",
            "coba : coba\n",
            "istana : istana\n",
            "adakan : adakan\n",
            "poling : poling\n",
            "nnbersediakah : nnbersediakah\n",
            "junto : junto\n",
            "pns : pns\n",
            "bdibangunnya : bdibangunnya\n",
            "beritamineral : beritamineral\n",
            "optimis : optimis\n",
            "bangkitkan : bangkit\n",
            "jokowibapakinfrastruktur : jokowibapakinfrastruktur\n",
            "pilpres : pilpres\n",
            "kpu : kpu\n",
            "menghitung : hitung\n",
            "suara : suara\n",
            "hiruk : hiruk\n",
            "pikuk : pikuk\n",
            "langkah : langkah\n",
            "berkembang : kembang\n",
            "bberitamineral : bberitamineral\n",
            "meningkat : tingkat\n",
            "tinulltinaaa : tinulltinaaa\n",
            "memajukan : maju\n",
            "nndki : nndki\n",
            "nkotaduniauntuksemua : nkotaduniauntuksemua\n",
            "megakumalasarie : megakumalasarie\n",
            "peringatan : ingat\n",
            "hut : hut\n",
            "peningkatan : tingkat\n",
            "keren : keren\n",
            "btiga : btiga\n",
            "berjalan : jalan\n",
            "lancar : lancar\n",
            "kendala : kendala\n",
            "mimpi : mimpi\n",
            "kecebong : kecebong\n",
            "anjing : anjing\n",
            "kejauhan : jauh\n",
            "gw : gw\n",
            "tw : tw\n",
            "kl : kl\n",
            "pemimpin : pimpin\n",
            "cukong : cukong\n",
            "nkri : nkri\n",
            "rusak : rusak\n",
            "menarik : tarik\n",
            "dikasih : kasih\n",
            "insentif : insentif\n",
            "periode : periode\n",
            "hguhgb : hguhgb\n",
            "dsb : dsb\n",
            "itupun : itu\n",
            "nandashanum : nandashanum\n",
            "bkeren : bkeren\n",
            "calon : calon\n",
            "bayo : bayo\n",
            "oicoffe : oicoffe\n",
            "berpotensi : potensi\n",
            "bikin : bikin\n",
            "teknologi : teknologi\n",
            "mantap : mantap\n",
            "tuh : tuh\n",
            "yuk : yuk\n",
            "positifekonomi : positifekonomi\n",
            "mensejahterakan : sejahtera\n",
            "bindonesia : bindonesia\n",
            "positif : positif\n",
            "bjiwatertukar : bjiwatertukar\n",
            "tingkatkan : tingkat\n",
            "bidang : bidang\n",
            "boicoffe : boicoffe\n",
            "pajakpajak : pajakpajak\n",
            "harga : harga\n",
            "ambisinya : ambisi\n",
            "byusufdumdum : byusufdumdum\n",
            "kantor : kantor\n",
            "pbnu : pbnu\n",
            "diresmikan : resmi\n",
            "mendkung : mendkung\n",
            "peluang : peluang\n",
            "potensi : potensi\n",
            "halal : halal\n",
            "hub : hub\n",
            "hilirisasi : hilir\n",
            "proaktif : proaktif\n",
            "zelenskyyua : zelenskyyua\n",
            "nawarin : nawarin\n",
            "tanah : tanah\n",
            "npliss : npliss\n",
            "impes : impes\n",
            "tu : tu\n",
            "mai : mai\n",
            "kantri : kantri\n",
            "terapkan : terap\n",
            "depanniknnusantarandukungiknnusantaraniknpemerataanekonomi : depanniknnusantarandukungiknnusantaraniknpemerataanekonomi\n",
            "positifterhadap : positifterhadap\n",
            "pemerataan : perata\n",
            "bawa : bawa\n",
            "positifke : positifke\n",
            "salam : salam\n",
            "bangga : bangga\n",
            "matang : matang\n",
            "siapkan : siap\n",
            "bus : bus\n",
            "semoga : moga\n",
            "bpapaloren : bpapaloren\n",
            "maaf : maaf\n",
            "nih : nih\n",
            "entar : entar\n",
            "ngisi : ngisi\n",
            "bahasa : bahasa\n",
            "lg : lg\n",
            "heuheu : heuheu\n",
            "jiwatertukar : jiwatertukar\n",
            "akademisi : akademisi\n",
            "ikut : ikut\n",
            "bkompastv : bkompastv\n",
            "elonmusk : elonmusk\n",
            "melebihi : lebih\n",
            "prastow : prastow\n",
            "holiday : holiday\n",
            "super : super\n",
            "deduction : deduction\n",
            "antusiasme : antusiasme\n",
            "publik : publik\n",
            "pasca : pasca\n",
            "market : market\n",
            "sounding : sounding\n",
            "isi : isi\n",
            "berdamaiwaduh : berdamaiwaduh\n",
            "malu : malu\n",
            "kali : kali\n",
            "berdamaimana : berdamaimana\n",
            "aq : aq\n",
            "yaa : yaa\n",
            "munafik : munafik\n",
            "bantu : bantu\n",
            "kreatif : kreatif\n",
            "bconfesstweetmy : bconfesstweetmy\n",
            "offshore : offshore\n",
            "xpnh : xpnh\n",
            "rsnya : rsnya\n",
            "kedeng : kedeng\n",
            "ngan : ngan\n",
            "osea : osea\n",
            "rate : rate\n",
            "usdday : usdday\n",
            "la : la\n",
            "bmakin : bmakin\n",
            "of : of\n",
            "indonesiannsumatera : indonesiannsumatera\n",
            "iknnnsulawesi : iknnnsulawesi\n",
            "unggulnnsulawesi : unggulnnsulawesi\n",
            "tengahnkotaduniauntuksemua : tengahnkotaduniauntuksemua\n",
            "bpgi : bpgi\n",
            "kukar : kukar\n",
            "nusantarannsulawesi : nusantarannsulawesi\n",
            "gerakan : gera\n",
            "lingkungannnsulawesi : lingkungannnsulawesi\n",
            "drpd : drpd\n",
            "bayaran : bayar\n",
            "mendingan : mending\n",
            "terhormat : hormat\n",
            "iknnbrg : iknnbrg\n",
            "suami : suami\n",
            "isteri : isteri\n",
            "binfrastruktur : binfrastruktur\n",
            "citynnsulawesi : citynnsulawesi\n",
            "bentuk : bentuk\n",
            "komitmen : komitmen\n",
            "berkelanjutan : lanjut\n",
            "nnsulawesi : nnsulawesi\n",
            "lingkungannnsumatera : lingkungannnsumatera\n",
            "sentrisnnsulawesi : sentrisnnsulawesi\n",
            "kebanggaan : bangga\n",
            "iknnnsumatera : iknnnsumatera\n",
            "nusanrtara : nusanrtara\n",
            "simbol : simbol\n",
            "kerukunan : rukun\n",
            "nusantarannsumatera : nusantarannsumatera\n",
            "bingung : bingung\n",
            "jg : jg\n",
            "krna : krna\n",
            "musim : musim\n",
            "kemarau : kemarau\n",
            "bersih : bersih\n",
            "magnet : magnet\n",
            "pertumbuhan : tumbuh\n",
            "usaha : usaha\n",
            "bkehadiran : bkehadiran\n",
            "bri : bri\n",
            "finlandia : finlandia\n",
            "kembangkan : kembang\n",
            "sepenuhnya : sepenuh\n",
            "kawal : kawal\n",
            "citynnsumatera : citynnsumatera\n",
            "mahasiswa : mahasiswa\n",
            "citynkotaduniauntuksemua : citynkotaduniauntuksemua\n",
            "nusantaranndki : nusantaranndki\n",
            "mengangkat : angkat\n",
            "kearifan : arif\n",
            "bpddk : bpddk\n",
            "positifnndki : positifnndki\n",
            "pariwisata : pariwisata\n",
            "pakar : pakar\n",
            "bertahap : tahap\n",
            "melibatkan : libat\n",
            "binilah : bini\n",
            "bkereennikn : bkereennikn\n",
            "btargetnya : btargetnya\n",
            "bzarazettirazr : bzarazettirazr\n",
            "sales : sales\n",
            "kalik : kalik\n",
            "lingkungan : lingkung\n",
            "disana : sana\n",
            "udaranya : udara\n",
            "segar : segar\n",
            "sehat : sehat\n",
            "bmanfaat : bmanfaat\n",
            "mengembangkan : kembang\n",
            "bhaktirah : bhaktirah\n",
            "mbaksri : mbaksri\n",
            "apapun : apa\n",
            "tuntutannya : tuntut\n",
            "mundur : mundur\n",
            "knpagar : knpagar\n",
            "batal : batal\n",
            "terealisasi : realisasi\n",
            "bhey : bhey\n",
            "rokok : rokok\n",
            "dongs : dongs\n",
            "respect : respect\n",
            "legend : legend\n",
            "banyaknya : banyak\n",
            "riang : riang\n",
            "terbuka : buka\n",
            "masyarakatkotaduniauntuksemua : masyarakatkotaduniauntuksemua\n",
            "hebatkotaduniauntuksemua : hebatkotaduniauntuksemua\n",
            "nusantarakotaduniauntuksemua : nusantarakotaduniauntuksemua\n",
            "majukan : maju\n",
            "indonesiakotaduniauntuksemua : indonesiakotaduniauntuksemua\n",
            "dimata : mata\n",
            "rakyatkotaduniauntuksemua : rakyatkotaduniauntuksemua\n",
            "perencanaan : rencana\n",
            "majukotaduniauntuksemua : majukotaduniauntuksemua\n",
            "balshaibashihab : balshaibashihab\n",
            "duitnya : duit\n",
            "bangunn : bangunn\n",
            "binfo : binfo\n",
            "citynnaceh : citynnaceh\n",
            "bmbaksri : bmbaksri\n",
            "iknnnaceh : iknnnaceh\n",
            "direncanakan : rencana\n",
            "diputuskan : putus\n",
            "rinnaceh : rinnaceh\n",
            "bwaw : bwaw\n",
            "wapres : wapres\n",
            "temui : temu\n",
            "bos : bos\n",
            "maruf : maruf\n",
            "diklaim : klaim\n",
            "percepat : cepat\n",
            "alasan : alas\n",
            "golkar : golkar\n",
            "airlangga : airlangga\n",
            "hartarto : hartarto\n",
            "duta : duta\n",
            "pemuda : pemuda\n",
            "sadar : sadar\n",
            "hukum : hukum\n",
            "ilmu : ilmu\n",
            "budaya : budaya\n",
            "songsong : songsong\n",
            "iknndihuni : iknndihuni\n",
            "sukses : sukses\n",
            "raksasa : raksasa\n",
            "properti : properti\n",
            "lirik : lirik\n",
            "itb : itb\n",
            "jalin : jalin\n",
            "kesepakatan : sepakat\n",
            "digitalisasi : digitalisasi\n",
            "komposisi : komposisi\n",
            "capai : capai\n",
            "men : men\n",
            "btancap : btancap\n",
            "gas : gas\n",
            "bandinilayla : bandinilayla\n",
            "bnews : bnews\n",
            "bginaoktorina : bginaoktorina\n",
            "positifpada : positifpada\n",
            "kelompok : kelompok\n",
            "heran : heran\n",
            "kotaku : kota\n",
            "berkonsepkan : konsep\n",
            "bkingparatha : bkingparatha\n",
            "gorontalo : gorontalo\n",
            "harus : harus\n",
            "bkonsep : bkonsep\n",
            "terbaik : baik\n",
            "didunia : dunia\n",
            "aminin : aminin\n",
            "sepaku : paku\n",
            "pengamanan : aman\n",
            "meninjau : tinjau\n",
            "hanya : hanya\n",
            "mengalami : alami\n",
            "pesat : pesat\n",
            "perekonomiannnikn : perekonomiannnikn\n",
            "bjagat : bjagat\n",
            "sadarlah : sadar\n",
            "indonesiatdk : indonesiatdk\n",
            "tuk : tuk\n",
            "berdiam : diam\n",
            "diriharus : diriharus\n",
            "bersatu : satu\n",
            "tolak : tolak\n",
            "omnibuslaw : omnibuslaw\n",
            "hip : hip\n",
            "iknuu : iknuu\n",
            "sensasi : sensasi\n",
            "alam : alam\n",
            "citynnikn : citynnikn\n",
            "bdaya : bdaya\n",
            "tampung : tampung\n",
            "tpa : tpa\n",
            "manggar : manggar\n",
            "bgorontalo : bgorontalo\n",
            "bagus : bagus\n",
            "citacita : citacita\n",
            "unggulnnikn : unggulnnikn\n",
            "sabar : sabar\n",
            "menunggu : tunggu\n",
            "bsemoga : bsemoga\n",
            "riau : riau\n",
            "bhalo : bhalo\n",
            "sobatkomibu : sobatkomibu\n",
            "memasuki : pasuk\n",
            "tahap : tahap\n",
            "lhonnapa : lhonnapa\n",
            "diterima : terima\n",
            "harusnya : harus\n",
            "uni : uni\n",
            "barangkali : barangkali\n",
            "penawaran : tawar\n",
            "nyoba : nyoba\n",
            "expansi : expansi\n",
            "australia : australia\n",
            "bnyatanya : bnyatanya\n",
            "musk : musk\n",
            "suka : suka\n",
            "beli : beli\n",
            "iknnpadahal : iknnpadahal\n",
            "mahalninvestor : mahalninvestor\n",
            "doakan : doa\n",
            "bmantap : bmantap\n",
            "iknnnikn : iknnnikn\n",
            "futur : futur\n",
            "bjumlah : bjumlah\n",
            "pengembang : kembang\n",
            "bnusa : bnusa\n",
            "tenggara : tenggara\n",
            "timurnikn : timurnikn\n",
            "merepresentasikan : representasi\n",
            "majunnikn : majunnikn\n",
            "rajaandalas : rajaandalas\n",
            "pgi : pgi\n",
            "iknnkepulauan : iknnkepulauan\n",
            "bangka : bangka\n",
            "majunkepulauan : majunkepulauan\n",
            "usharanimuni : usharanimuni\n",
            "kawan : kawan\n",
            "nusantarankepulauan : nusantarankepulauan\n",
            "bmari : bmari\n",
            "torang : torang\n",
            "didukung : dukung\n",
            "bmantapntiga : bmantapntiga\n",
            "unggulnkepulauan : unggulnkepulauan\n",
            "paknnikn : paknnikn\n",
            "berkat : berkat\n",
            "sejahterakan : sejahtera\n",
            "indonesiankepulauan : indonesiankepulauan\n",
            "bjika : bjika\n",
            "president : president\n",
            "merasakakan : merasakakan\n",
            "kesusahan : susah\n",
            "penderitaan : derita\n",
            "sebaiknya : baik\n",
            "lingkungannnikn : lingkungannnikn\n",
            "kutai : kuta\n",
            "kartanegara : kartanegara\n",
            "btarget : btarget\n",
            "diperoleh : oleh\n",
            "bbentuk : bbentuk\n",
            "merataverse : merataverse\n",
            "btetap : btetap\n",
            "aspek : aspek\n",
            "poin : poin\n",
            "kontrol : kontrol\n",
            "ditinggalkan : tinggal\n",
            "pantesan : pantesan\n",
            "bdukungan : bdukungan\n",
            "tap : tap\n",
            "disematkan : semat\n",
            "btorng : btorng\n",
            "tergetkan : tergetkan\n",
            "daerah : daerah\n",
            "penopang : topang\n",
            "bmerepresentasikan : bmerepresentasikan\n",
            "unggul : unggul\n",
            "wujud : wujud\n",
            "bibu : bibu\n",
            "jati : jati\n",
            "indonesiannsulawesi : indonesiannsulawesi\n",
            "bwahh : bwahh\n",
            "nusantarannwarganet : nusantarannwarganet\n",
            "bada : bada\n",
            "data : data\n",
            "ditutupisebaiknya : ditutupisebaiknya\n",
            "dibuka : buka\n",
            "carut : carut\n",
            "marutnya : marut\n",
            "pengelolaan : kelola\n",
            "masuknya : masuk\n",
            "membantu : bantu\n",
            "arsjadrasjid : arsjadrasjid\n",
            "iknnusantara : iknnusantara\n",
            "inklusifkolaboratif : inklusifkolaboratif\n",
            "menyambut : sambut\n",
            "bpoeamran : bpoeamran\n",
            "realisasi : realisasi\n",
            "emang : emang\n",
            "memenuhi : penuh\n",
            "target : target\n",
            "bong : bong\n",
            "lingkungannnwarganet : lingkungannnwarganet\n",
            "indonesianikn : indonesianikn\n",
            "nusantaran : nusantaran\n",
            "nikn : nikn\n",
            "citynnwarganet : citynnwarganet\n",
            "bprogres : bprogres\n",
            "bsukseskan : bsukseskan\n",
            "terbukti : bukti\n",
            "bkeuangannewsid : bkeuangannewsid\n",
            "musti : musti\n",
            "ngutus : ngutus\n",
            "prabowo : prabowo\n",
            "sederhana : sederhana\n",
            "ketemu : ketemu\n",
            "membanggakan : bangga\n",
            "pembanguna : pembanguna\n",
            "bmantaap : bmantaap\n",
            "buntuk : buntuk\n",
            "perkembangan : kembang\n",
            "bkita : bkita\n",
            "tuntas : tuntas\n",
            "perekenomian : perekenomian\n",
            "sentris : sentris\n",
            "pemerintahan : perintah\n",
            "penandatangan : penandatangan\n",
            "kontraktor : kontraktor\n",
            "perolehan : oleh\n",
            "nilai : nilai\n",
            "buppdate : buppdate\n",
            "drun : drun\n",
            "targetnya : target\n",
            "doang : doang\n",
            "salmakiandra : salmakiandra\n",
            "giginpraginanto : giginpraginanto\n",
            "akar : akar\n",
            "rumput : rumput\n",
            "no : no\n",
            "way : way\n",
            "bbangnalar : bbangnalar\n",
            "mngkinmreka : mngkinmreka\n",
            "iknprcpat : iknprcpat\n",
            "boneka : boneka\n",
            "mamarika : mamarika\n",
            "bngung : bngung\n",
            "demonya : demo\n",
            "bkorban : bkorban\n",
            "iknnudah : iknnudah\n",
            "kerasa : rasa\n",
            "hawa : hawa\n",
            "gerahnya : gerah\n",
            "cooy : cooy\n",
            "panasgile : panasgile\n",
            "menawarkan : tawar\n",
            "senin : senin\n",
            "naik : naik\n",
            "brakyat : brakyat\n",
            "kejayaan : jaya\n",
            "bwah : bwah\n",
            "surodilagan : surodilagan\n",
            "democrazymedia : democrazymedia\n",
            "gedunggedung : gedunggedung\n",
            "swasta : swasta\n",
            "januari : januari\n",
            "pemesan : mes\n",
            "ngributin : ngributin\n",
            "formulasmntr : formulasmntr\n",
            "nombok : nombok\n",
            "trilyunan : trilyunan\n",
            "laporan : lapor\n",
            "dr : dr\n",
            "mandalika : mandalika\n",
            "nusa : nusa\n",
            "timurnpemindahan : timurnpemindahan\n",
            "harapan : harap\n",
            "bospurwa : bospurwa\n",
            "silakan : sila\n",
            "simak : simak\n",
            "video : video\n",
            "inindulu : inindulu\n",
            "esemka : esemka\n",
            "beda : beda\n",
            "tipis : tipis\n",
            "tukang : tukang\n",
            "obat : obat\n",
            "pinggir : pinggir\n",
            "elinaazkia : elinaazkia\n",
            "banget : banget\n",
            "curiga : curiga\n",
            "bengkakpuas : bengkakpuas\n",
            "lingkungannndaerah : lingkungannndaerah\n",
            "istimewa : istimewa\n",
            "iknnndaerah : iknnndaerah\n",
            "indonesianndaerah : indonesianndaerah\n",
            "bdalam : bdalam\n",
            "pertemuan : temu\n",
            "menpora : menpora\n",
            "zainudin : zainudin\n",
            "amali : amal\n",
            "melaporkan : lapor\n",
            "kementerian : menteri\n",
            "representasu : representasu\n",
            "unggulnndaerah : unggulnndaerah\n",
            "desain : desain\n",
            "citynndaerah : citynndaerah\n",
            "keuarkan : uar\n",
            "bkmi : bkmi\n",
            "dewan : dewan\n",
            "adat : adat\n",
            "dayak : dayak\n",
            "cbg : cbg\n",
            "barat : barat\n",
            "pemb : pemb\n",
            "kmi : kmi\n",
            "tdk : tdk\n",
            "prnah : prnah\n",
            "mmnta : mmnta\n",
            "dpndhkan : dpndhkan\n",
            "bsuruh : bsuruh\n",
            "daracega : daracega\n",
            "nnbiar : nnbiar\n",
            "produk : produk\n",
            "unggulan : unggul\n",
            "bdan : bdan\n",
            "mala : mala\n",
            "sibuk : sibuk\n",
            "ditengah : tengah\n",
            "rakyatnya : rakyat\n",
            "masuk : masuk\n",
            "syurga : syurga\n",
            "pintu : pintu\n",
            "ojiyuu : ojiyuu\n",
            "ingin : ingin\n",
            "butuh : butuh\n",
            "roket : roket\n",
            "tulisan : tulis\n",
            "ranisudibyo : ranisudibyo\n",
            "besarbesarannnmenurut : besarbesarannnmenurut\n",
            "bambang : bambang\n",
            "kepala : kepala\n",
            "bsegera : bsegera\n",
            "bursa : bursa\n",
            "bsbk : bsbk\n",
            "tangkap : tangkap\n",
            "bisnis : bisnis\n",
            "terbaru : baru\n",
            "kaukutangkap : tangkap\n",
            "susantono : susantono\n",
            "fisik : fisik\n",
            "besarbesaran : besarbesaran\n",
            "nidyaluna : nidyaluna\n",
            "nnpersiapan : nnpersiapan\n",
            "dilakukam : dilakukam\n",
            "besarbesaean : besarbesaean\n",
            "geloraco : geloraco\n",
            "bnandashanum : bnandashanum\n",
            "suciranii : suciranii\n",
            "momentum : momentum\n",
            "pembangunanikn : pembangunanikn\n",
            "bbalikpapan : bbalikpapan\n",
            "dhahana : dhahana\n",
            "putra : putra\n",
            "plt : plt\n",
            "pp : pp\n",
            "didampingi : damping\n",
            "cahyani : cahyani\n",
            "suryandari : suryandari\n",
            "dir : dir\n",
            "perancangan : ancang\n",
            "peraturan : atur\n",
            "infrastructure : infrastructure\n",
            "metropolis : metropolis\n",
            "tujuannya : tuju\n",
            "ngundang : ngundang\n",
            "ribuan : ribu\n",
            "desa : desa\n",
            "pake : pake\n",
            "duit : duit\n",
            "pribadi : pribadi\n",
            "nkan : nkan\n",
            "triliun : triliun\n",
            "ticket : ticket\n",
            "akomodasi : akomodasi\n",
            "bhermawandevina : bhermawandevina\n",
            "milih : milih\n",
            "ngeluarin : ngeluarin\n",
            "ketimbang : ketimbang\n",
            "stabilisasi : stabilisasi\n",
            "ea : ea\n",
            "tembus : tembus\n",
            "rupiah : rupiah\n",
            "terpuruk : puruk\n",
            "nangan : nang\n",
            "angannya : angan\n",
            "nkantrok : nkantrok\n",
            "nera : nera\n",
            "habibie : habibie\n",
            "belasan : bas\n",
            "tercermin : cermin\n",
            "baspek : baspek\n",
            "syukur : syukur\n",
            "jgjadiklonya : jgjadiklonya\n",
            "ntar : ntar\n",
            "disuruh : suruh\n",
            "loo : loo\n",
            "setuju : tuju\n",
            "fi : fi\n",
            "dilanjutkan : lanjut\n",
            "byang : byang\n",
            "bkepulauan : bkepulauan\n",
            "belitung : belitung\n",
            "byogisaputrahd : byogisaputrahd\n",
            "nusantaranndaerah : nusantaranndaerah\n",
            "yogyakartanikn : yogyakartanikn\n",
            "umkmnkepulauan : umkmnkepulauan\n",
            "bmedsossamson : bmedsossamson\n",
            "terbaiknndaerah : terbaiknndaerah\n",
            "bmengintip : bmengintip\n",
            "positifnndaerah : positifnndaerah\n",
            "bukti : bukti\n",
            "bkota : bkota\n",
            "kek : kek\n",
            "urgensinya : urgensi\n",
            "jalur : jalur\n",
            "kuat : kuat\n",
            "tonggak : tonggak\n",
            "majunndaerah : majunndaerah\n",
            "hebatnndaerah : hebatnndaerah\n",
            "indonesianpapua : indonesianpapua\n",
            "bertahapnpapua : bertahapnpapua\n",
            "briau : briau\n",
            "support : support\n",
            "lingkungannpapua : lingkungannpapua\n",
            "bsahabatpp : bsahabatpp\n",
            "beriringan : iring\n",
            "menguntungkan : untung\n",
            "membeli : beli\n",
            "bro : bro\n",
            "karna : karna\n",
            "omset : omset\n",
            "perbulan : bulan\n",
            "jayanndaerah : jayanndaerah\n",
            "bsejumlah : bsejumlah\n",
            "bduta : bduta\n",
            "mengganggu : ganggu\n",
            "nsumatera : nsumatera\n",
            "teknogav : teknogav\n",
            "sajikan : saji\n",
            "virtual : virtual\n",
            "terhubung : hubung\n",
            "bbersiaplah : bbersiaplah\n",
            "citynsumatera : citynsumatera\n",
            "hidupkan : hidup\n",
            "bmasyarkat : bmasyarkat\n",
            "bjoss : bjoss\n",
            "jaga : jaga\n",
            "bsemua : bsemua\n",
            "terkena : kena\n",
            "positifpembangunan : positifpembangunan\n",
            "nvroost : nvroost\n",
            "kalangan : kalang\n",
            "nusnatara : nusnatara\n",
            "an : an\n",
            "positifnkepulauan : positifnkepulauan\n",
            "mandaat : mandaat\n",
            "bmantab : bmantab\n",
            "platmirah : platmirah\n",
            "menghuni : huni\n",
            "nusantarankotaduniauntuksemua : nusantarankotaduniauntuksemua\n",
            "anakn : anakn\n",
            "cerdas : cerdas\n",
            "bbambang : bbambang\n",
            "menyebut : sebut\n",
            "strategi : strategi\n",
            "bmembanggakan : bmembanggakan\n",
            "citynkepulauan : citynkepulauan\n",
            "bhantamanhitam : bhantamanhitam\n",
            "solusi : solusi\n",
            "damai : damai\n",
            "populasi : populasi\n",
            "berteknologi : teknologi\n",
            "canggihnkepulauan : canggihnkepulauan\n",
            "bresesi : bresesi\n",
            "niknat : niknat\n",
            "dustakan : dusta\n",
            "bburnoxyz : bburnoxyz\n",
            "perlindungan : lindung\n",
            "sosial : sosial\n",
            "rapbn : rapbn\n",
            "nominalnyanaik : nominalnyanaik\n",
            "bjokoei : bjokoei\n",
            "iknnnkalimantan : iknnnkalimantan\n",
            "bnaomisusantiiii : bnaomisusantiiii\n",
            "pengen : ken\n",
            "ndukungiknnusantara : ndukungiknnusantara\n",
            "lingkungannnkalimantan : lingkungannnkalimantan\n",
            "identitas : identitas\n",
            "indonesiannkalimantan : indonesiannkalimantan\n",
            "berpengaruh : pengaruh\n",
            "arab : arab\n",
            "papua : papua\n",
            "bdari : bdari\n",
            "saudi : saudi\n",
            "berpeluang : peluang\n",
            "mendapatkan : dapat\n",
            "menopang : topang\n",
            "kebutuhan : butuh\n",
            "kana : kana\n",
            "bmasuknya : bmasuknya\n",
            "maluku : malu\n",
            "bhadirnya : bhadirnya\n",
            "delegasi : delegasi\n",
            "berinvenstasi : berinvenstasi\n",
            "bpada : bpada\n",
            "memiliki : milik\n",
            "menghadiri : hadir\n",
            "konferensi : konferensi\n",
            "bterbaik : bterbaik\n",
            "bhubungan : bhubungan\n",
            "dipertahankan : tahan\n",
            "presentasi : presentasi\n",
            "bajakan : baja\n",
            "bketika : bketika\n",
            "rayu : rayu\n",
            "sultan : sultan\n",
            "jajak : jajak\n",
            "pasar : pasar\n",
            "bjangan : bjangan\n",
            "pastikan : pasti\n",
            "keamanan : aman\n",
            "si : si\n",
            "ber : ber\n",
            "ktt : ktt\n",
            "selamat : selamat\n",
            "pm : pm\n",
            "inggris : inggris\n",
            "bktt : bktt\n",
            "dinilai : nilai\n",
            "bdeklarasi : bdeklarasi\n",
            "menteri : menteri\n",
            "digital : digital\n",
            "demm : demm\n",
            "bpersatuan : bpersatuan\n",
            "insinyur : insinyur\n",
            "menginisialisasi : inisial\n",
            "terbentuknya : bentuk\n",
            "bsiapa : bsiapa\n",
            "peserta : serta\n",
            "recovertogetherrecoverstronger : recovertogetherrecoverstronger\n",
            "aviation : aviation\n",
            "dialogue : dialogue\n",
            "hasilkan : hasil\n",
            "prioritas : prioritas\n",
            "brevitalisasi : brevitalisasi\n",
            "tmii : tmii\n",
            "persiapan : siap\n",
            "presidensi : presidensi\n",
            "nusantarannmalut : nusantarannmalut\n",
            "bsukses : bsukses\n",
            "masbronnu : masbronnu\n",
            "bkepala : bkepala\n",
            "bhebat : bhebat\n",
            "infrastrukturn : infrastrukturn\n",
            "nnmalut : nnmalut\n",
            "tni : tni\n",
            "polri : polri\n",
            "lingkungannnmalut : lingkungannnmalut\n",
            "timurnkomitmen : timurnkomitmen\n",
            "ulama : ulama\n",
            "malut : malut\n",
            "bsambutan : bsambutan\n",
            "oktober : oktober\n",
            "youtube : youtube\n",
            "cukup : cukup\n",
            "baiknnibu : baiknnibu\n",
            "dikotori : kotor\n",
            "abuwaras : abuwaras\n",
            "voc : voc\n",
            "menikmati : nikmat\n",
            "batavia : batavia\n",
            "tahunnnkeprok : tahunnnkeprok\n",
            "barudak : barudak\n",
            "sindaisalie : sindaisalie\n",
            "kelestarian : lestari\n",
            "nnyg : nnyg\n",
            "menentang : tentang\n",
            "bgenerasi : bgenerasi\n",
            "muda : muda\n",
            "terwujudnya : wujud\n",
            "hadirnya : hadir\n",
            "ntapi : ntapi\n",
            "nyinyir : nyinyir\n",
            "suku : suku\n",
            "dihina : hina\n",
            "tp : tp\n",
            "terang : terang\n",
            "ngak : ngak\n",
            "tunda : tunda\n",
            "kah : kah\n",
            "asboedionoid : asboedionoid\n",
            "prestasi : prestasi\n",
            "dibanggakan : bangga\n",
            "semesta : semesta\n",
            "nasib : nasib\n",
            "dialami : alami\n",
            "catatankaqihati : catatankaqihati\n",
            "nsampai : nsampai\n",
            "masuki : masuk\n",
            "tahapan : tahap\n",
            "land : land\n",
            "wuiih : wuiih\n",
            "anggarkan : anggar\n",
            "hampir : hampir\n",
            "mnjasa : mnjasa\n",
            "konsultansi : konsultansi\n",
            "anidraayt : anidraayt\n",
            "bpn : bpn\n",
            "bcatatankaqihati : bcatatankaqihati\n",
            "galerifitri : galerifitri\n",
            "tahapndan : tahapndan\n",
            "dlm : dlm\n",
            "pembersihan : bersih\n",
            "bkerukunan : bkerukunan\n",
            "etnis : etnis\n",
            "batak : batak\n",
            "karo : karo\n",
            "simalem : simalem\n",
            "bontang : bontang\n",
            "adl : adl\n",
            "sulit : sulit\n",
            "dibantah : ban\n",
            "bhw : bhw\n",
            "berniat : niat\n",
            "raja : raja\n",
            "nnngga : nnngga\n",
            "bforjakeu : bforjakeu\n",
            "joss : joss\n",
            "forjakeu : forjakeu\n",
            "ditinjau : tinjau\n",
            "nusantarannpresiden : nusantarannpresiden\n",
            "ae : ae\n",
            "nek : nek\n",
            "rumitikn : rumitikn\n",
            "noviroose : noviroose\n",
            "pemkab : pemkab\n",
            "iknnndiskominfo : iknnndiskominfo\n",
            "kabupaten : kabupaten\n",
            "dafip : dafip\n",
            "haryanto : haryanto\n",
            "kemenpu : kemenpu\n",
            "halo : halo\n",
            "sahabatpupr : sahabatpupr\n",
            "dinas : dinas\n",
            "kominfo : kominfo\n",
            "bkadrun : bkadrun\n",
            "takut : takut\n",
            "dayakmakanya : dayakmakanya\n",
            "bmwlorg : bmwlorg\n",
            "promosiin : promosiin\n",
            "tarik : tarik\n",
            "tahunmantappp : tahunmantappp\n",
            "bkotanusantara : bkotanusantara\n",
            "akornas : akornas\n",
            "pemerataaan : pemerataaan\n",
            "alisyarief : alisyarief\n",
            "teenangjanuari : teenangjanuari\n",
            "gedung : gedung\n",
            "dah : dah\n",
            "nampak : nampak\n",
            "kotanusantara : kotanusantara\n",
            "derap : derap\n",
            "semangatnusantara : semangatnusantara\n",
            "bkalimantan : bkalimantan\n",
            "helmifelis : helmifelis\n",
            "gaakan : gaakan\n",
            "laku : laku\n",
            "kangakuy : kangakuy\n",
            "kacep : kacep\n",
            "jktbdgcoret : jktbdgcoret\n",
            "stop : stop\n",
            "pemilupilkada : pemilupilkada\n",
            "on : on\n",
            "schedule : schedule\n",
            "sesuai : sesuai\n",
            "amanat : amanat\n",
            "uunsetelah : uunsetelah\n",
            "bteddgus : bteddgus\n",
            "urgennmisal : urgennmisal\n",
            "golkarpedia : golkarpedia\n",
            "hetifah : hetifah\n",
            "penguatan : kuat\n",
            "sdm : sdm\n",
            "oongroni : oongroni\n",
            "nenek : nenek\n",
            "lampir : lampir\n",
            "ngebacotkemarin : ngebacotkemarin\n",
            "ribut : ribut\n",
            "ijazah : ijazah\n",
            "ketahuan : tahu\n",
            "bohong : bohong\n",
            "cuitan : cuit\n",
            "hapus : hapus\n",
            "ngebacot : ngebacot\n",
            "dakhnan : dakhnan\n",
            "burhanmuhtadi : burhanmuhtadi\n",
            "yunartowijaya : yunartowijaya\n",
            "saifulmujani : saifulmujani\n",
            "dppnasdem : dppnasdem\n",
            "pdiperjuangan : pdiperjuangan\n",
            "model : model\n",
            "perpolitikan : politik\n",
            "haji : haji\n",
            "gunakan : guna\n",
            "haranamardjihad : haranamardjihad\n",
            "habiskan : habis\n",
            "hutang : hutang\n",
            "sepatutnya : patut\n",
            "kades : kades\n",
            "bdoktertifa : bdoktertifa\n",
            "ghaib : ghaib\n",
            "oligarki : oligarki\n",
            "reformasi : reformasi\n",
            "berlanjut : lanjut\n",
            "aburojoo : aburojoo\n",
            "lha : lha\n",
            "trus : trus\n",
            "ngapainnapa : ngapainnapa\n",
            "dsruh : dsruh\n",
            "bkin : bkin\n",
            "tenan : tenan\n",
            "iinasurbakti : iinasurbakti\n",
            "iknnsigapmembangunnegeri : iknnsigapmembangunnegeri\n",
            "lanjooot : lanjooot\n",
            "terjunnya : terjun\n",
            "wisata : wisata\n",
            "doadoa : doadoa\n",
            "terlibat : libat\n",
            "lindungan : lindung\n",
            "allah : allah\n",
            "swt : swt\n",
            "enam : enam\n",
            "seindonesia : indonesia\n",
            "kunjungi : kunjung\n",
            "bkitaadlidn : bkitaadlidn\n",
            "kadal : kadal\n",
            "otaknya : otak\n",
            "sampe : sampe\n",
            "kesinicoba : kesinicoba\n",
            "palestina : palestina\n",
            "semuakadal : semuakadal\n",
            "bvivacoid : bvivacoid\n",
            "seharusnyari : seharusnyari\n",
            "tuan : tuan\n",
            "penyelenggaraan : selenggara\n",
            "dg : dg\n",
            "balisyarief : balisyarief\n",
            "katanyapunya : katanyapunya\n",
            "subsidi : subsidi\n",
            "dicabut : cabut\n",
            "nyatanyancuma : nyatanyancuma\n",
            "nafsu : nafsu\n",
            "bfinlandia : bfinlandia\n",
            "berminat : minat\n",
            "versi : versi\n",
            "virtualniknnusantarandukungiknnusantaraniknsejahterakanindonesia : virtualniknnusantarandukungiknnusantaraniknsejahterakanindonesia\n",
            "polhuk : polhuk\n",
            "dumeh : dumeh\n",
            "opo : opo\n",
            "guna : guna\n",
            "lgsg : lgsg\n",
            "kelar : kelar\n",
            "candi : candi\n",
            "prambanan : prambanan\n",
            "bberbagai : bberbagai\n",
            "bsutanmangara : bsutanmangara\n",
            "pemberitaan : berita\n",
            "napa : napa\n",
            "nsedangkan : nsedangkan\n",
            "imcmushroom : imcmushroom\n",
            "mikir : mikir\n",
            "nbuat : nbuat\n",
            "manfaatnyanbanyak : manfaatnyanbanyak\n",
            "kelaparanemangnya : kelaparanemangnya\n",
            "pergi : pergi\n",
            "kesana : kesana\n",
            "hidayatnatari : hidayatnatari\n",
            "dananya : dana\n",
            "mananduitnya : mananduitnya\n",
            "mananmemangnya : mananmemangnya\n",
            "perjalanan : jalan\n",
            "rumit : rumit\n",
            "ataurumit : ataurumit\n",
            "rumitkan : rumit\n",
            "knp : knp\n",
            "justrupaksakan : justrupaksakan\n",
            "antaranews : antaranews\n",
            "dijadwalkan : jadwal\n",
            "national : national\n",
            "capital : capital\n",
            "bsabut : bsabut\n",
            "patuhprokesselalusehat : patuhprokesselalusehat\n",
            "kunjungan : kunjung\n",
            "bseandainya : bseandainya\n",
            "ngibulnnmau : ngibulnnmau\n",
            "pulau : pulau\n",
            "ane : ane\n",
            "dukungnnkloperlu : dukungnnkloperlu\n",
            "nusakambangan : nusakambangan\n",
            "jadiin : jadiin\n",
            "pemanis : man\n",
            "diskon : diskon\n",
            "bnichosilalahi : bnichosilalahi\n",
            "bergerak : gerak\n",
            "keras : keras\n",
            "dijual : jual\n",
            "cina : cina\n",
            "rezim : rezim\n",
            "olgarki : olgarki\n",
            "ms : ms\n",
            "agusyudhoyono : agusyudhoyono\n",
            "meeting : meeting\n",
            "bongnkelas : bongnkelas\n",
            "pencitraan : citra\n",
            "wakil : wakil\n",
            "bleonitalestari : bleonitalestari\n",
            "ilustrasinya : ilustrasi\n",
            "sepatu : sepatu\n",
            "kulit : kulit\n",
            "bryawiedy : bryawiedy\n",
            "peduli : peduli\n",
            "ngutang : ngutang\n",
            "ngemis : ngemis\n",
            "gadaikan : gadai\n",
            "walapun : walapun\n",
            "susah : susah\n",
            "bsekalian : bsekalian\n",
            "toll : toll\n",
            "dihentikan : henti\n",
            "keyword : keyword\n",
            "penghematan : hemat\n",
            "penasehat : nasehat\n",
            "tony : tony\n",
            "blair : blair\n",
            "terkuat : kuat\n",
            "duniannsehun : duniannsehun\n",
            "jt : jt\n",
            "merdeka : merdeka\n",
            "timurncakwmenlanyallaacademynnibukotanegara : timurncakwmenlanyallaacademynnibukotanegara\n",
            "timurnindiaknowledgeniknidnnibukotanegara : timurnindiaknowledgeniknidnnibukotanegara\n",
            "bderap : bderap\n",
            "nusantarannalarininstituteniknnusantaraidnnibukotanegara : nusantarannalarininstituteniknnusantaraidnnibukotanegara\n",
            "emas : emas\n",
            "nusantaranfordamailnceriaceritakitannibukotanegara : nusantaranfordamailnceriaceritakitannibukotanegara\n",
            "bstevaniehuangg : bstevaniehuangg\n",
            "alhamdulillahnsemoga : alhamdulillahnsemoga\n",
            "keluarganya : keluarga\n",
            "iknjangan : iknjangan\n",
            "bpipri : bpipri\n",
            "kemenkopmk : kemenkopmk\n",
            "getol : getol\n",
            "nibukotanegaraniknnsemangatnusantara : nibukotanegaraniknnsemangatnusantara\n",
            "selasa : selasa\n",
            "dijamin : jamin\n",
            "bahagia : bahagia\n",
            "dng : dng\n",
            "tergantung : gantung\n",
            "menekan : tekan\n",
            "senilai : nila\n",
            "biki : bik\n",
            "gabisa : gabisa\n",
            "pecah : pecah\n",
            "dadi : dadi\n",
            "sumatra : sumatra\n",
            "bali : bal\n",
            "riegosee : riegosee\n",
            "keberadaan : ada\n",
            "penandatanganan : penandatanganan\n",
            "ngerokok : ngerokok\n",
            "pagiii : pagiii\n",
            "btokoh : btokoh\n",
            "agama : agama\n",
            "indon : indon\n",
            "dukunikn : dukunikn\n",
            "hafalmengingat : hafalmengingat\n",
            "isis : isis\n",
            "serbaguna : serbaguna\n",
            "terrorist : terrorist\n",
            "awangawang : awangawang\n",
            "membumikan : bumi\n",
            "superhub : superhub\n",
            "klaster : klaster\n",
            "penopangnyanklaster : penopangnyanklaster\n",
            "bersihnklaster : bersihnklaster\n",
            "farmasi : farmasi\n",
            "keluarga : keluarga\n",
            "bgalerifitri : bgalerifitri\n",
            "brizkidwika : brizkidwika\n",
            "nf : nf\n",
            "cabang : cabang\n",
            "matamu : mata\n",
            "picek : picek\n",
            "brinindonesia : brinindonesia\n",
            "bpupr : bpupr\n",
            "dkijakarta : dkijakarta\n",
            "sepeda : sepeda\n",
            "diperuntukkan : untuk\n",
            "melanda : landa\n",
            "wajib : wajib\n",
            "bpt : bpt\n",
            "raih : raih\n",
            "terima : terima\n",
            "nmenpora : nmenpora\n",
            "bpemkab : bpemkab\n",
            "bkalo : bkalo\n",
            "perencana : rencana\n",
            "rebutan : rebut\n",
            "kue : kue\n",
            "rahasia : rahasia\n",
            "mateng : mateng\n",
            "centra : centra\n",
            "ngab : ngab\n",
            "roselasetia : roselasetia\n",
            "peluncuran : luncur\n",
            "doankwarto : doankwarto\n",
            "mahal : mahal\n",
            "iknnnternyata : iknnnternyata\n",
            "penanganan : tangan\n",
            "indonselalu : indonselalu\n",
            "terdepan : depan\n",
            "iblis : iblis\n",
            "blis : blis\n",
            "dandhylaksono : dandhylaksono\n",
            "gampang : gampang\n",
            "stadion : stadion\n",
            "standar : standar\n",
            "fifa : fifa\n",
            "sirkuit : sirkuit\n",
            "balap : balap\n",
            "premiumnnlalu : premiumnnlalu\n",
            "afrizamunaf : afrizamunaf\n",
            "tngkl : tngkl\n",
            "berterima : terima\n",
            "jokowihebat : jokowihebat\n",
            "polresta : polresta\n",
            "balam : balam\n",
            "suwandaben : suwandaben\n",
            "iknnpromotornya : iknnpromotornya\n",
            "ketua : ketua\n",
            "dpp : dpp\n",
            "apdesi : apdesi\n",
            "surtawijayannjokowi : surtawijayannjokowi\n",
            "bditinjau : bditinjau\n",
            "th : th\n",
            "tifa : tifa\n",
            "tidur : tidur\n",
            "nyenyak : nyenyak\n",
            "pakde : pakde\n",
            "top : top\n",
            "baikarif : baikarif\n",
            "hariankompas : hariankompas\n",
            "spt : spt\n",
            "pd : pd\n",
            "fokus : fokus\n",
            "cpt : cpt\n",
            "bsindaisalie : bsindaisalie\n",
            "jatah : jatah\n",
            "makax : makax\n",
            "bulux : bulux\n",
            "diatas : atas\n",
            "rencanakan : rencana\n",
            "datangkan : datang\n",
            "melegetimasi : melegetimasi\n",
            "bwh : bwh\n",
            "bimcmushroom : bimcmushroom\n",
            "puas : puas\n",
            "mengiklankan : iklan\n",
            "media : media\n",
            "karnamungkin : karnamungkin\n",
            "kedatangan : datang\n",
            "bya : bya\n",
            "mimpin : mimpin\n",
            "sekarangnnanti : sekarangnnanti\n",
            "anis : anis\n",
            "presidentnstop : presidentnstop\n",
            "kompromi : kompromi\n",
            "naudit : naudit\n",
            "muhammadsaewad : muhammadsaewad\n",
            "garagara : garagara\n",
            "babuwaras : babuwaras\n",
            "gorila : gorila\n",
            "bicara : bicara\n",
            "ngerti : ngerti\n",
            "bkejaksaan : bkejaksaan\n",
            "dokter : dokter\n",
            "iknn : iknn\n",
            "ntt : ntt\n",
            "pendukung : dukung\n",
            "buzzerp : buzzerp\n",
            "senyap : senyap\n",
            "urusan : urus\n",
            "bherrikusnadi : bherrikusnadi\n",
            "ucapkan : ucap\n",
            "kebohongan : bohong\n",
            "jgn : jgn\n",
            "bebrbasis : bebrbasis\n",
            "fakta : fakta\n",
            "bhelmifelis : bhelmifelis\n",
            "mukidi : mukidi\n",
            "wafatpun : wafat\n",
            "adajadi : adajadi\n",
            "ngandeng : ngandeng\n",
            "kejaksaannkementerian : kejaksaannkementerian\n",
            "puprn : puprn\n",
            "pantau : pantau\n",
            "speedtrap : speedtrap\n",
            "milik : milik\n",
            "kafir : kafir\n",
            "main : main\n",
            "tl : tl\n",
            "keadilan : adil\n",
            "berbangsa : bangsa\n",
            "biayanya : biaya\n",
            "indonesiannikn : indonesiannikn\n",
            "kehilangan : hilang\n",
            "cucu : cucu\n",
            "terampas : ampas\n",
            "krisis : krisis\n",
            "biknid : biknid\n",
            "bnawaninik : bnawaninik\n",
            "ronialkhoir : ronialkhoir\n",
            "chusnulch : chusnulch\n",
            "faktakonsep : faktakonsep\n",
            "banjir : banjir\n",
            "sponge : sponge\n",
            "lu : lu\n",
            "qontol : qontol\n",
            "keuntungannya : untung\n",
            "kemana : mana\n",
            "semudah : mudah\n",
            "dibayangkan : bayang\n",
            "ad : ad\n",
            "al : al\n",
            "au : au\n",
            "perluasan : luas\n",
            "alutisnya : alutisnya\n",
            "melingkari : lingkar\n",
            "nyatakan : nyata\n",
            "tanam : tanam\n",
            "cuplikan : cuplik\n",
            "sepekan : pek\n",
            "nnpresiden : nnpresiden\n",
            "pekan : pekan\n",
            "persis : persis\n",
            "sd : sd\n",
            "ttg : ttg\n",
            "abis : abis\n",
            "radarkorupsi : radarkorupsi\n",
            "isu : isu\n",
            "gulita : gulita\n",
            "menunda : tunda\n",
            "periodenndan : periodenndan\n",
            "bplatform : bplatform\n",
            "gambaran : gambar\n",
            "nyata : nyata\n",
            "argumenmu : argumen\n",
            "cm : cm\n",
            "ngandelin : ngandelin\n",
            "issue : issue\n",
            "maksa : maksa\n",
            "kepastian : pasti\n",
            "trs : trs\n",
            "migrasi : migrasi\n",
            "kapal : kapal\n",
            "om : om\n",
            "klu : klu\n",
            "bdaripada : bdaripada\n",
            "kesehatan : sehat\n",
            "ekonominbukan : ekonominbukan\n",
            "jopermadi : jopermadi\n",
            "sampeyan : sampeyan\n",
            "contoh : contoh\n",
            "bandingin : bandingin\n",
            "kalsel : kalsel\n",
            "bahas : bahas\n",
            "diluncurkan : luncur\n",
            "niknsejahterakanindonesia : niknsejahterakanindonesia\n",
            "gilaaa : gilaaa\n",
            "kadesntapi : kadesntapi\n",
            "nengok : nengok\n",
            "fotofoto : fotofoto\n",
            "nkalo : nkalo\n",
            "hotel : hotel\n",
            "yasonnab : yasonnab\n",
            "barunindonesia : barunindonesia\n",
            "barunnindonesia : barunnindonesia\n",
            "membutuhkan : butuh\n",
            "adil : adil\n",
            "bsirqieee : bsirqieee\n",
            "kelamin : kelamin\n",
            "mrk : mrk\n",
            "tahunya : tahu\n",
            "msh : msh\n",
            "iknnniknberdampakpositif : iknnniknberdampakpositif\n",
            "bojk : bojk\n",
            "keuangan : uang\n",
            "berkantor : kantor\n",
            "bsalah : bsalah\n",
            "bsatriohendri : bsatriohendri\n",
            "kecilan : kecil\n",
            "ta : ta\n",
            "kantong : kantong\n",
            "kipp : kipp\n",
            "bseperti : bseperti\n",
            "pepatahnpengacara : pepatahnpengacara\n",
            "argonya : argonya\n",
            "pendek : pendek\n",
            "pepatah : pepatah\n",
            "ngkongroses : ngkongroses\n",
            "olahraga : olahraga\n",
            "bfull : bfull\n",
            "tank : tank\n",
            "hilang : hilang\n",
            "panggung : panggung\n",
            "habib : habib\n",
            "ayuwulandariz : ayuwulandariz\n",
            "bu : bu\n",
            "bmodus : bmodus\n",
            "dipakainnbiaya : dipakainnbiaya\n",
            "triliunnnklik : triliunnnklik\n",
            "baca : baca\n",
            "plis : plis\n",
            "my : my\n",
            "bsinergi : bsinergi\n",
            "sampah : sampah\n",
            "bpietfitriady : bpietfitriady\n",
            "ameliarfk : ameliarfk\n",
            "kerakyatan : rakyat\n",
            "nusantaranberdampak : nusantaranberdampak\n",
            "timurnnniknberdampakpositif : timurnnniknberdampakpositif\n",
            "dikembangkan : kembang\n",
            "barundukung : barundukung\n",
            "nusantarannniknberdampakpositif : nusantarannniknberdampakpositif\n",
            "nusantaranuntuk : nusantaranuntuk\n",
            "sentrisnujar : sentrisnujar\n",
            "jokowinnniknberdampakpositif : jokowinnniknberdampakpositif\n",
            "bsatiagustaman : bsatiagustaman\n",
            "impor : impor\n",
            "umbar : umbar\n",
            "wkwkwk : wkwkwk\n",
            "anthonybudiawan : anthonybudiawan\n",
            "softbank : softbank\n",
            "disahkan : sah\n",
            "ahmaddshaddiq : ahmaddshaddiq\n",
            "dukun : dukun\n",
            "capitalism : capitalism\n",
            "privilege : privilege\n",
            "etalase : etalase\n",
            "hegemoni : hegemoni\n",
            "oligarkinnjokowi : oligarkinnjokowi\n",
            "terjebak : jebak\n",
            "budi : budi\n",
            "danannkarena : danannkarena\n",
            "diadili : adil\n",
            "kaplingkan : kapling\n",
            "apart : apart\n",
            "salesmarketingnya : salesmarketingnya\n",
            "dibantai : bantai\n",
            "selesainnsesederhana : selesainnsesederhana\n",
            "itunnmakanya : itunnmakanya\n",
            "sirik : sirik\n",
            "ngga : ngga\n",
            "kebagian : bagi\n",
            "wuuiiihhh : wuuiiihhh\n",
            "mendoakan : doa\n",
            "umurnmari : umurnmari\n",
            "beliau : beliau\n",
            "umur : umur\n",
            "pinter : pinter\n",
            "gibrantweet : gibrantweet\n",
            "njokowi : njokowi\n",
            "platform : platform\n",
            "fitur : fitur\n",
            "btawarkan : btawarkan\n",
            "brayu : brayu\n",
            "menurunkn : menurunkn\n",
            "bala : bala\n",
            "tentara : tentara\n",
            "menjajah : jajah\n",
            "menurunkan : turun\n",
            "jutaan : juta\n",
            "diazputransyah : diazputransyah\n",
            "duniannnnnia : duniannnnnia\n",
            "bisu : bisu\n",
            "tercemar : cemar\n",
            "secepatnya : cepat\n",
            "steril : steril\n",
            "mabuk : mabuk\n",
            "radikalis : radikal\n",
            "intoleran : intoleran\n",
            "sdhlah : sdhlah\n",
            "sebar : sebar\n",
            "hoax : hoax\n",
            "melulunindonesia : melulunindonesia\n",
            "utuh : utuh\n",
            "konstitusinya : konstitusi\n",
            "dijunjung : junjung\n",
            "bkementrian : bkementrian\n",
            "modalnniknberdampakpositif : modalnniknberdampakpositif\n",
            "orangorang : orangorang\n",
            "kepentingan : penting\n",
            "berpindahnya : pindah\n",
            "kebanyakan : banyak\n",
            "sok : sok\n",
            "perduli : duli\n",
            "marbunpm : marbunpm\n",
            "tuduhan : tuduh\n",
            "membabibuta : membabibuta\n",
            "mshin : mshin\n",
            "uunya : uunya\n",
            "terangggg : terangggg\n",
            "terusssss : terusssss\n",
            "bravo : bravo\n",
            "bpk : bpk\n",
            "jangan : jangan\n",
            "buzzerbab : buzzerbab\n",
            "adlh : adlh\n",
            "bmeninggalkan : bmeninggalkan\n",
            "legacy : legacy\n",
            "sepenting : penting\n",
            "meninggalkan : tinggal\n",
            "amalan : amal\n",
            "jariyah : jariyah\n",
            "jelajah : jelajah\n",
            "nnjagatnusantara : nnjagatnusantara\n",
            "hebatnya : hebat\n",
            "urgen : urgen\n",
            "bbakpiaduren : bbakpiaduren\n",
            "idextratime : idextratime\n",
            "kendor : kendor\n",
            "bela : bela\n",
            "sajatapi : sajatapi\n",
            "harjonoabi : harjonoabi\n",
            "projectmorg : projectmorg\n",
            "iknid : iknid\n",
            "didesain : desain\n",
            "manusiamanusia : manusiamanusia\n",
            "penghuninya : hun\n",
            "mengakomodir : mengakomodir\n",
            "ketar : ketar\n",
            "ketir : tir\n",
            "satupun : satu\n",
            "kubu : kubu\n",
            "berpikir : pikir\n",
            "jokowin : jokowin\n",
            "bmusniumar : bmusniumar\n",
            "ahok : ahok\n",
            "kau : kau\n",
            "nikmati : nikmat\n",
            "drunm : drunm\n",
            "biarkan : biar\n",
            "generasi : generasi\n",
            "btxtdarihi : btxtdarihi\n",
            "bayarnya : bayar\n",
            "suntikan : sunti\n",
            "iknkereta : iknkereta\n",
            "membebani : beban\n",
            "bsaat : bsaat\n",
            "inkonstitusionalisasi : inkonstitusional\n",
            "kehidupan : hidup\n",
            "bernegara : negara\n",
            "memupuk : pupuk\n",
            "koalisi : koalisi\n",
            "buzzerrp : buzzerrp\n",
            "goblok : goblok\n",
            "uyokback : uyokback\n",
            "tewas : tewas\n",
            "lubang : lubang\n",
            "bekas : bekas\n",
            "tambang : tambang\n",
            "takdirnyan : takdirnyan\n",
            "anakanak : anakanak\n",
            "bprojectmorg : bprojectmorg\n",
            "btanah : btanah\n",
            "dikuasai : asai\n",
            "kapitalis : kapitalis\n",
            "tipikal : tipikal\n",
            "indah : indah\n",
            "kap : kap\n",
            "kayaknya : kayak\n",
            "mojadi : mojadi\n",
            "free : free\n",
            "for : for\n",
            "bbisakah : bbisakah\n",
            "berminatnini : berminatnini\n",
            "tetangga : tetangga\n",
            "bli : bli\n",
            "tanahsana : tanahsana\n",
            "mengatasi : atas\n",
            "memangnya : memang\n",
            "mambangun : mambangun\n",
            "jkt : jkt\n",
            "tempo : tempo\n",
            "mengejar : kejar\n",
            "track : track\n",
            "record : record\n",
            "nasdem : nasdem\n",
            "membela : bela\n",
            "sang : sang\n",
            "penista : nista\n",
            "bbm : bbm\n",
            "omnibus : omnibus\n",
            "law : law\n",
            "oh : oh\n",
            "bkn : bkn\n",
            "jargon : jargon\n",
            "politik : politik\n",
            "deh : deh\n",
            "pemeretaan : eta\n",
            "bforum : bforum\n",
            "bakohumas : bakohumas\n",
            "diperlukan : perlu\n",
            "informasi : informasi\n",
            "sobatkom : sobatkom\n",
            "diskominfokaltim : diskominfokaltim\n",
            "bgarenghallu : bgarenghallu\n",
            "gitu : gitu\n",
            "mangkrak : mangkrak\n",
            "loh : loh\n",
            "ditundabukan : ditundabukan\n",
            "jln : jln\n",
            "widodoec : widodoec\n",
            "paham : paham\n",
            "sejarahnya : sejarah\n",
            "bkangl : bkangl\n",
            "haus : haus\n",
            "hausteh : hausteh\n",
            "tolteh : tolteh\n",
            "tolyang : tolyang\n",
            "lapar : lapar\n",
            "roti : roti\n",
            "iknnroti : iknnroti\n",
            "nnkita : nnkita\n",
            "anggap : anggap\n",
            "urgent : urgent\n",
            "memperluas : luas\n",
            "siswa : siswa\n",
            "kelulusan : kelulus\n",
            "buang : buang\n",
            "fungsinya : fungsi\n",
            "kurang : kurang\n",
            "menyuntikkan : suntik\n",
            "keterpurukan : puruk\n",
            "kesulitan : sulit\n",
            "adrasilent : adrasilent\n",
            "alas : alas\n",
            "kaki : kaki\n",
            "kedepak : depak\n",
            "nhebat : nhebat\n",
            "dijaman : jam\n",
            "laseapoyhbb : laseapoyhbb\n",
            "bmenpora : bmenpora\n",
            "bjokowipres : bjokowipres\n",
            "hrs : hrs\n",
            "dibelintetap : dibelintetap\n",
            "tirtoid : tirtoid\n",
            "memperoleh : oleh\n",
            "selesai : selesai\n",
            "duluan : duluan\n",
            "iknng : iknng\n",
            "munafiklah : munafik\n",
            "cnnindonesia : cnnindonesia\n",
            "hatihati : hatihati\n",
            "umurnya : umur\n",
            "angkut : angkut\n",
            "kekayaan : kaya\n",
            "bumi : bumi\n",
            "ka : ka\n",
            "bnapsu : bnapsu\n",
            "engga : engga\n",
            "warasnikn : warasnikn\n",
            "pintar : pintar\n",
            "diperbodoh : bodoh\n",
            "kemampuan : mampu\n",
            "pikirannya : pikir\n",
            "gankofpetojo : gankofpetojo\n",
            "difoto : foto\n",
            "mrt : mrt\n",
            "blokgedung : blokgedung\n",
            "kejaksaan : jaksa\n",
            "agung : agung\n",
            "berdiri : diri\n",
            "tegak : tegak\n",
            "lbh : lbh\n",
            "terbakarnnrakyat : terbakarnnrakyat\n",
            "boleh : boleh\n",
            "mymine : mymine\n",
            "ni : ni\n",
            "kang : kang\n",
            "edi : edi\n",
            "mulyadi : mulyadi\n",
            "kadung : kadung\n",
            "gegara : gegara\n",
            "protes : protes\n",
            "gaterima : gaterima\n",
            "jk : jk\n",
            "tergusur : gusur\n",
            "belanda : belanda\n",
            "kuasai : kuasa\n",
            "berperang : perang\n",
            "ambisi : ambisi\n",
            "berkoar : koar\n",
            "kasta : kasta\n",
            "bani : bani\n",
            "bipang : bipang\n",
            "penghuni : huni\n",
            "kelak : kelak\n",
            "perkawinan : kawin\n",
            "babi : babi\n",
            "keputusan : putus\n",
            "memicu : picu\n",
            "perbincangan : bincang\n",
            "perihal : perihal\n",
            "nama : nama\n",
            "bkontenislamcom : bkontenislamcom\n",
            "bcamarxoxo : bcamarxoxo\n",
            "nusantaranjambinkotaduniauntuksemua : nusantaranjambinkotaduniauntuksemua\n",
            "bdariatigunawan : bdariatigunawan\n",
            "babangmeme : babangmeme\n",
            "bgunakan : bgunakan\n",
            "logika : logika\n",
            "ganti : ganti\n",
            "presidenbukan : presidenbukan\n",
            "pdip : pdip\n",
            "direzim : rezim\n",
            "bpart : bpart\n",
            "ngamuk : ngamuk\n",
            "gara : gara\n",
            "ditunda : tunda\n",
            "kebal : kebal\n",
            "nipu : nipu\n",
            "negerikolam : negerikolam\n",
            "gelombang : gelombang\n",
            "iii : iii\n",
            "pencaplokan : caplok\n",
            "batas : batas\n",
            "hak : hak\n",
            "tumbuh : tumbuh\n",
            "partai : partai\n",
            "komunis : komunis\n",
            "china : china\n",
            "imigrasi : imigrasi\n",
            "wna : wna\n",
            "second : second\n",
            "home : home\n",
            "visa : visa\n",
            "memancing : pancing\n",
            "tiongkok : tiongkok\n",
            "hubungannya : hubung\n",
            "kesanaapa : kesanaapa\n",
            "daerahnya : daerah\n",
            "jga : jga\n",
            "bersifat : sifat\n",
            "bsentil : bsentil\n",
            "lanyalla : lanyalla\n",
            "ingatkan : ingat\n",
            "prioritaskan : prioritas\n",
            "lanyallaacademy : lanyallaacademy\n",
            "mengumpulkan : kumpul\n",
            "nmasih : nmasih\n",
            "ingatkah : ingat\n",
            "metverse : metverse\n",
            "bernama : nama\n",
            "awalpembiayaan : awalpembiayaan\n",
            "sokong : sokong\n",
            "bapln : bapln\n",
            "premium : premium\n",
            "{'brt': 'brt', 'alshaibashihab': 'alshaibashihab', 'indonesia': 'indonesia', 'ditangan': 'tang', 'presiden': 'presiden', 'jokowi': 'jokowi', 'bendungan': 'bendung', 'ruas': 'ruas', 'jalan': 'jalan', 'bandara': 'bandara', 'barunsirkuit': 'barunsirkuit', 'mandalikankereta': 'mandalikankereta', 'api': 'api', 'bprathumryan': 'bprathumryan', 'pranjayabaguz': 'pranjayabaguz', 'buset': 'buset', 'miliar': 'miliar', 'usd': 'usd', 'kalahin': 'kalahin', 'anggaran': 'anggar', 'militer': 'militer', 'bener': 'bener', 'yah': 'yah', 'sih': 'sih', 'maksain': 'maksain', 'bangun': 'bangun', 'ikn': 'ikn', 'msaiddidu': 'msaiddidu', 'pddk': 'pddk', 'yg': 'yg', 'asn': 'asn', 'gajinya': 'gaji', 'sdh': 'sdh', 'habis': 'habis', 'utk': 'utk', 'cicilan': 'cicil', 'rumah': 'rumah', 'kendaraan': 'kendara', 'biaya': 'biaya', 'anak': 'anak', 'sekolah': 'sekolah', 'shg': 'shg', 'hendryanalubis': 'hendryanalubis', 'pasti': 'pasti', 'mendukung': 'dukung', 'sapa': 'sapa', 'bisa': 'bisa', 'lanjutkan': 'lanjut', 'orang': 'orang', 'berani': 'berani', 'gk': 'gk', 'kalo': 'kalo', 'pindah': 'pindah', 'kalimnatannnburuan': 'kalimnatannnburuan', 'bpemerintah': 'bpemerintah', 'susun': 'susun', 'rencana': 'rencana', 'pengembangan': 'kembang', 'infrastruktur': 'infrastruktur', 'hunian': 'huni', 'penting': 'penting', 'entaskan': 'entas', 'kemiskinan': 'miskin', 'mas': 'mas', 'joko': 'joko', 'menggenaskan': 'menggenaskan', 'masse': 'masse', 'menyusun': 'susun', 'penduduk': 'duduk', 'kota': 'kota', 'nusantara': 'nusantara', 'bzackyramadhani': 'bzackyramadhani', 'nanya': 'nanya', 'fungsi': 'fungsi', 'biar': 'biar', 'ku': 'ku', 'kasih': 'kasih', 'tau': 'tau', 'ya': 'ya', 'salah': 'salah', 'upaya': 'upaya', 'keuangannewsid': 'keuangannewsid', 'buntu': 'buntu', 'dampak': 'dampak', 'positifbagi': 'positifbagi', 'kemajuan': 'maju', 'bangsa': 'bangsa', 'gak': 'gak', 'demo': 'demo', 'bohirnya': 'bohirnya', 'memikirkan': 'pikir', 'tinggal': 'tinggal', 'ibukota': 'ibukota', 'representasi': 'representasi', 'guzelamare': 'guzelamare', 'iyalah': 'iya', 'twitter': 'twitter', 'mah': 'mah', 'kliatan': 'kliatan', 'visi': 'visi', 'misi': 'misi', 'nya': 'nya', 'investor': 'investor', 'blm': 'blm', 'mau': 'mau', 'bp': 'bp', 'sbg': 'sbg', 'markreting': 'markreting', 'berkelas': 'kelas', 'internasional': 'internasional', 'bcnnindonesia': 'bcnnindonesia', 'ngebet': 'ngebet', 'pejabat': 'jabat', 'silahkan': 'silah', 'aja': 'aja', 'pakai': 'pakai', 'uang': 'uang', 'hasil': 'hasil', 'korupsi': 'korupsi', 'ditindak': 'tindak', 'serius': 'serius', 'bmendukung': 'bmendukung', 'mengawal': 'awal', 'terus': 'terus', 'pemindahan': 'pindah', 'bergetarnusa': 'bergetarnusa', 'maryshelparaiso': 'maryshelparaiso', 'arek': 'arek', 'jawa': 'jawa', 'timur': 'timur', 'dukung': 'dukung', 'pembangunan': 'bangun', 'kotaduniauntuksemua': 'kotaduniauntuksemua', 'bikn': 'bikn', 'berkonsep': 'konsep', 'ramah': 'ramah', 'bpembangunan': 'bpembangunan', 'dilaksanakan': 'laksana', 'bdukung': 'bdukung', 'mpr': 'mpr', 'ri': 'ri', 'keluarkan': 'keluar', 'ketetapan': 'tetap', 'bberikut': 'bberikut', 'manfaat': 'manfaat', 'perekonomian': 'ekonomi', 'positifuntuk': 'positifuntuk', 'aceh': 'aceh', 'hadir': 'hadir', 'targetkan': 'target', 'dihuni': 'huni', 'bpresiden': 'bpresiden', 'meluncurkan': 'luncur', 'jagat': 'jagat', 'metaverse': 'metaverse', 'green': 'green', 'bteguhsd': 'bteguhsd', 'ih': 'ih', 'ko': 'ko', 'ngeyel': 'ngeyel', 'bmsaiddidu': 'bmsaiddidu', 'gimana': 'gimana', 'ngitungnya': 'ngitungnya', 'rb': 'rb', 'warga': 'warga', 'ngimpi': 'ngimpi', 'kok': 'kok', 'keterlaluan': 'terlalu', 'ragilsemar': 'ragilsemar', 'diawali': 'awal', 'konsep': 'konsep', 'pendanaan': 'dana', 'menjadikan': 'jadi', 'pemerintah': 'perintah', 'penyewa': 'sewa', 'ntentu': 'ntentu', 'bbergetarnusa': 'bbergetarnusa', 'membuka': 'buka', 'lapangan': 'lapang', 'kerja': 'kerja', 'masyarakat': 'masyarakat', 'kesejahteraan': 'sejahtera', 'boposisicerdas': 'boposisicerdas', 'baik': 'baik', 'gubernur': 'gubernur', 'fgelael': 'fgelael', 'dibangunnya': 'bangun', 'elemen': 'elemen', 'membawa': 'bawa', 'bdamri': 'bdamri', 'hadirkan': 'hadir', 'rute': 'rute', 'balikpapanikn': 'balikpapanikn', 'tarifnya': 'tarif', 'rp': 'rp', 'bmaryshelparaiso': 'bmaryshelparaiso', 'saya': 'saya', 'asli': 'asli', 'untung': 'untung', 'invest': 'invest', 'ourlittleboyz': 'ourlittleboyz', 'bfgelael': 'bfgelael', 'dibangun': 'bangun', 'irmansyahadhy': 'irmansyahadhy', 'jualan': 'jual', 'esemkaskrg': 'esemkaskrg', 'iknnsebenarx': 'iknnsebenarx', 'cebong': 'cebong', 'kemarin': 'kemarin', 'pilih': 'pilih', 'makelar': 'makelar', 'smart': 'smart', 'city': 'city', 'siap': 'siap', 'bersaing': 'saing', 'doktertifa': 'doktertifa', 'badai': 'badai', 'dunia': 'dunia', 'gelap': 'gelap', 'resesi': 'resesi', 'dahsyat': 'dahsyat', 'rawan': 'rawan', 'pangan': 'pangan', 'hebat': 'hebat', 'nnkenapa': 'nnkenapa', 'masih': 'masih', 'ngotot': 'ngotot', 'bsaudaraku': 'bsaudaraku', 'sebangsa': 'bangsa', 'setanah': 'tanah', 'air': 'air', 'kesadaran': 'sadar', 'manusia': 'manusia', 'waras': 'waras', 'meningkatkan': 'tingkat', 'ekonomi': 'ekonomi', 'bengkulu': 'bengkulu', 'mendorong': 'dorong', 'yaniarsim': 'yaniarsim', 'obral': 'obral', 'investasi': 'investasi', 'hgb': 'hgb', 'thn': 'thn', 'bebas': 'bebas', 'pajak': 'pajak', 'disc': 'disc', 'nkini': 'nkini', 'khusus': 'khusus', 'danai': 'dana', 'iknnkere': 'iknnkere', 'bkeran': 'bkeran', 'luncurkan': 'luncur', 'nusantaranibukotanegaraniknnsemangatnusantara': 'nusantaranibukotanegaraniknnsemangatnusantara', 'sasmojon': 'sasmojon', 'oposisicerdas': 'oposisicerdas', 'saking': 'saking', 'nggak': 'nggak', 'lakunya': 'laku', 'iknnmending': 'iknnmending', 'program': 'program', 'transmigrasi': 'transmigrasi', 'jaman': 'jaman', 'kiyaimarufamin': 'kiyaimarufamin', 'kesempatan': 'sempat', 'mengajak': 'ajak', 'dubai': 'dubai', 'holding': 'holding', 'menanamkan': 'tanam', 'sektor': 'sektor', 'dipikirkan': 'pikir', 'kelas': 'kelas', 'menengah': 'tengah', 'bawag': 'bawag', 'menjerit': 'jerit', 'akibat': 'akibat', 'byaniarsim': 'byaniarsim', 'aniesbaswedan': 'aniesbaswedan', 'gagal': 'gagal', 'kayak': 'kayak', 'dki': 'dki', 'tidak': 'tidak', 'teruskan': 'terus', 'maju': 'maju', 'bmaruf': 'bmaruf', 'pusat': 'pusat', 'industri': 'industri', 'tangan': 'tangan', 'ganjarpranowo': 'ganjarpranowo', 'nti': 'nti', 'landasan': 'landas', 'dpt': 'dpt', 'disempurnakan': 'sempurna', 'bpaltiwest': 'bpaltiwest', 'negeri': 'negeri', 'pemilu': 'milu', 'menang': 'menang', 'bukan': 'bukan', 'jagoannya': 'jago', 'negara': 'negara', 'bselama': 'bselama', 'penguasa': 'kuasa', 'berkuasa': 'kuasa', 'seringkali': 'seringkali', 'enggan': 'enggan', 'menerima': 'terima', 'masukan': 'masuk', 'saran': 'saran', 'nasihat': 'nasihat', 'twiter': 'twiter', 'untungikn': 'untungikn', 'ja': 'ja', 'dgn': 'dgn', 'asemka': 'asemka', 'bmembuka': 'bmembuka', 'bindra': 'bindra', 'karya': 'karya', 'garap': 'garap', 'proyek': 'proyek', 'dasar': 'dasar', 'wajah': 'wajah', 'mata': 'mata', 'ptppid': 'ptppid', 'uppdate': 'uppdate', 'balikpapan': 'balikpapan', 'ptpp': 'ptpp', 'menandatangani': 'menandatangani', 'kontrak': 'kontrak', 'pekerjaan': 'kerja', 'eropa': 'eropa', 'nangis': 'nang', 'liat': 'liat', 'batu': 'batu', 'bara': 'bara', 'dijadikan': 'jadi', 'dinding': 'dinding', 'pembatas': 'batas', 'btxtdrpemerintah': 'btxtdrpemerintah', 'dibanding': 'banding', 'pendidikan': 'didik', 'ingatlah': 'ingat', 'menyetujui': 'tuju', 'amp': 'amp', 'mengesyahkan': 'syah', 'nnjangan': 'nnjangan', 'tenggelamkan': 'tenggelam', 'udahbangun': 'udahbangun', 'cepetannasn': 'cepetannasn', 'cepetan': 'cepetan', 'suruh': 'suruh', 'pindahngw': 'pindahngw', 'proyeksikan': 'proyeksi', 'muncul': 'muncul', 'bgeloraco': 'bgeloraco', 'ayo': 'ayo', 'apbn': 'apbn', 'kereta': 'kereta', 'cepat': 'cepat', 'mobil': 'mobil', 'listriknnga': 'listriknnga', 'ribu': 'ribu', 'presidennya': 'presiden', 'yogaswarawahyu': 'yogaswarawahyu', 'batalkan': 'batal', 'sy': 'sy', 'rakyat': 'rakyat', 'ide': 'ide', 'penjara': 'penjara', 'bairkamiid': 'bairkamiid', 'lama': 'lama', 'jakarta': 'jakarta', 'berkurang': 'kurang', 'pindang': 'pindang', 'bdetikcom': 'bdetikcom', 'seramai': 'serama', 'terkait': 'kait', 'provinsi': 'provinsi', 'kalimantan': 'kalimantan', 'menjalin': 'jalin', 'update': 'update', 'progres': 'progres', 'timurnnberikut': 'timurnnberikut', 'kita': 'kita', 'btheschloss': 'btheschloss', 'santorinissun': 'santorinissun', 'stefanantonio': 'stefanantonio', 'outofthebay': 'outofthebay', 'guoblokkknnikn': 'guoblokkknnikn', 'kcic': 'kcic', 'blampung': 'blampung', 'percaya': 'percaya', 'perubahan': 'ubah', 'bmasyarakat': 'bmasyarakat', 'lampung': 'lampung', 'bpemindahan': 'bpemindahan', 'sejarah': 'sejarah', 'tersendiri': 'sendiri', 'keuntungan': 'untung', 'berkah': 'berkah', 'peroleh': 'oleh', 'perpindahan': 'pindah', 'kebijakan': 'bijak', 'btopansolawase': 'btopansolawase', 'sirqieee': 'sirqieee', 'mahfud': 'mahfud', 'diuntungkansapa': 'diuntungkansapa', 'dirugikan': 'rugi', 'mayan': 'mayan', 'dana': 'dana', 'ubah': 'ubah', 'uu': 'uu', 'jkw': 'jkw', 'pembagian': 'bagi', 'sda': 'sda', 'timpang': 'timpang', 'ndak': 'ndak', 'kekurangan': 'kurang', 'tak': 'tak', 'rela': 'rela', 'uangnya': 'uang', 'dipakai': 'pakai', 'bayar': 'bayar', 'utang': 'utang', 'hukumdan': 'hukumdan', 'bowoendarto': 'bowoendarto', 'yaqutcqoumas': 'yaqutcqoumas', 'yaqutqoumas': 'yaqutqoumas', 'bodoh': 'bodoh', 'kaya': 'kaya', 'loe': 'loe', 'bwapres': 'bwapres', 'tawarkan': 'tawar', 'petinggi': 'petinggi', 'bfransiskusjurin': 'bfransiskusjurin', 'durian': 'durian', 'kompom': 'kompom', 'amin': 'amin', 'ajak': 'ajak', 'berinvestasi': 'investasi', 'bkadin': 'bkadin', 'berharap': 'harap', 'badan': 'badan', 'otorita': 'otorita', 'detail': 'detail', 'paket': 'paket', 'investasinarsjad': 'investasinarsjad', 'rasjid': 'rasjid', 'inklusifkolab': 'inklusifkolab', 'arsjad': 'arsjad', 'pengusaha': 'usaha', 'global': 'global', 'forum': 'forum', 'november': 'november', 'buka': 'buka', 'lokal': 'lokal', 'berpartisipasi': 'partisipasi', 'papaloren': 'papaloren', 'temen': 'temen', 'sodara': 'sodara', 'tante': 'tante', 'ponakan': 'ponakan', 'adek': 'adek', 'mertus': 'mertus', 'jetli': 'jetli', 'bermanfaat': 'manfaat', 'umkm': 'umkm', 'mari': 'mari', 'celoteh': 'celoteh', 'bluar': 'bluar', 'dukungan': 'dukung', 'proses': 'proses', 'berdampak': 'dampak', 'positifdukung': 'positifdukung', 'strategis': 'strategis', 'memperkenalkan': 'kenal', 'percepatan': 'cepat', 'bseluruh': 'bseluruh', 'jayalah': 'jaya', 'indonesiaku': 'indonesia', 'bkami': 'bkami', 'berkomitmen': 'komitmen', 'penuh': 'penuh', 'menjaga': 'jaga', 'kondusif': 'kondusif', 'wilayah': 'wilayah', 'kelancaran': 'lancar', 'iknsejahterakanindonesia': 'iknsejahterakanindonesia', 'iknpemerataanekonomi': 'iknpemerataanekonomi', 'birhamnapermana': 'birhamnapermana', 'kasi': 'kasi', 'export': 'export', 'layak': 'layak', 'woy': 'woy', 'merata': 'rata', 'bwarga': 'bwarga', 'ikntingkatkankesejahteraan': 'ikntingkatkankesejahteraan', 'dukungiknnusantara': 'dukungiknnusantara', 'bsurat': 'bsurat', 'penunjukan': 'tunjuk', 'penyedia': 'sedia', 'barangjasa': 'barangjasa', 'pelaksanaan': 'laksana', 'manajemen': 'manajemen', 'konstruksi': 'konstruksi', 'induk': 'induk', 'kegiatan': 'giat', 'kadin': 'kadin', 'nusantaranarsjad': 'nusantaranarsjad', 'bpelaksanaan': 'bpelaksanaan', 'pengadaan': 'ada', 'barang': 'barang', 'jasa': 'jasa', 'dimana': 'mana', 'pt': 'pt', 'indra': 'indra', 'persero': 'persero', 'bjokowi': 'bjokowi', 'nusantaranpresiden': 'nusantaranpresiden', 'jokowinnaceh': 'jokowinnaceh', 'teguhsd': 'teguhsd', 'terwujud': 'wujud', 'bgok': 'bgok', 'ari': 'ari', 'perusahaan': 'usaha', 'berperan': 'peran', 'meminimalisir': 'meminimalisir', 'risiko': 'risiko', 'mencapai': 'capai', 'tujuan': 'tuju', 'kami': 'kami', 'memperhatikan': 'perhati', 'mutu': 'mutu', 'bangunan': 'bangun', 'bsejalan': 'bsejalan', 'pernyataan': 'nyata', 'dirjen': 'dirjen', 'cipta': 'cipta', 'direktur': 'direktur', 'utama': 'utama', 'gok': 'gok', 'joso': 'joso', 'simamora': 'simamora', 'bkapolres': 'bkapolres', 'ppu': 'ppu', 'sambut': 'sambut', 'wakapolda': 'wakapolda', 'kaltim': 'kaltim', 'rangka': 'rangka', 'tinjau': 'tinjau', 'bkerennikn': 'bkerennikn', 'perpresentasi': 'presentasi', 'unggulnnaceh': 'unggulnnaceh', 'bpantes': 'bpantes', 'oligar': 'oligar', 'panik': 'panik', 'tanda': 'tanda', 'buzzer': 'buzzer', 'membabi': 'babi', 'buta': 'buta', 'pengiringan': 'iring', 'narasi': 'narasi', 'sesat': 'sesat', 'nyanjk': 'nyanjk', 'bkementerian': 'bkementerian', 'perumahan': 'rumah', 'pupr': 'pupr', 'merancang': 'rancang', 'bertujuan': 'tuju', 'mengintegrasikan': 'integrasi', 'mentransformasikan': 'transformasi', 'lingkungannhanya': 'lingkungannhanya', 'hijaunsisanya': 'hijaunsisanya', 'korantempo': 'korantempo', 'pdb': 'pdb', 'nilainya': 'nilai', 'arunariftan': 'arunariftan', 'hnurwahid': 'hnurwahid', 'gardagerilyagp': 'gardagerilyagp', 'provokasi': 'provokasi', 'org': 'org', 'ga': 'ga', 'sejalan': 'jalan', 'mafia': 'mafia', 'laksanakan': 'laksana', 'beratahap': 'beratahap', 'mengusung': 'usung', 'future': 'future', 'iknnkotaduniauntuksemua': 'iknnkotaduniauntuksemua', 'bsiap': 'bsiap', 'menanti': 'nanti', 'tersohor': 'sohor', 'btak': 'btak', 'dipungkiri': 'dipungkiri', 'kehadiran': 'hadir', 'dorong': 'dorong', 'boptimis': 'boptimis', 'wujudkan': 'wujud', 'berkunjung': 'kunjung', 'kawasan': 'kawasan', 'jalannya': 'jalan', 'lahan': 'lahan', 'persemaian': 'semai', 'akses': 'akses', 'bmemajukan': 'bmemajukan', 'membangun': 'bangun', 'bsemakin': 'bsemakin', 'ramai': 'ramai', 'byakin': 'byakin', 'positifkotaduniauntuksemua': 'positifkotaduniauntuksemua', 'antusias': 'antusias', 'positifnkotaduniauntuksemua': 'positifnkotaduniauntuksemua', 'bfuture': 'bfuture', 'forest': 'forest', 'peradaban': 'adab', 'terpandang': 'pandang', 'lingkungannkotaduniauntuksemua': 'lingkungannkotaduniauntuksemua', 'unggulnkotaduniauntuksemua': 'unggulnkotaduniauntuksemua', 'nasionalnkotaduniauntuksemua': 'nasionalnkotaduniauntuksemua', 'zelensky': 'zelensky', 'bilang': 'bilang', 'udah': 'udah', 'urus': 'urus', 'mampu': 'mampu', 'mw': 'mw', 'negera': 'negera', 'sdg': 'sdg', 'konflik': 'konflik', 'pla': 'pla', 'terkatung': 'katung', 'nyaiibubu': 'nyaiibubu', 'klo': 'klo', 'iknsaya': 'iknsaya', 'yakin': 'yakin', 'mayoritas': 'mayoritas', 'jd': 'jd', 'pengangguran': 'anggur', 'job': 'job', 'ongkosi': 'ongkos', 'transport': 'transport', 'fix': 'fix', 'haram': 'haram', 'hukumnya': 'hukum', 'kadrun': 'kadrun', 'hidup': 'hidup', 'bnyaiibubu': 'bnyaiibubu', 'ferlynorman': 'ferlynorman', 'ramlirizal': 'ramlirizal', 'bang': 'bang', 'noam': 'noam', 'chomsky': 'chomsky', 'modern': 'modern', 'state': 'state', 'ankiiim': 'ankiiim', 'prof': 'prof', 'firman': 'firman', 'noor': 'noor', 'anies': 'anies', 'kandidat': 'kandidat', 'capres': 'capres', 'lawan': 'lawan', 'sm': 'sm', 'proffirman': 'proffirman', 'cuma': 'cuma', 'elon': 'elon', 'emoh': 'emoh', 'krn': 'krn', 'bengkak': 'bengkak', 'bolak': 'bolak', 'ditipu': 'tipu', 'pasrah': 'pasrah', 'beropa': 'opa', 'dipaksa': 'paksa', 'inves': 'inves', 'wkwk': 'wkwk', 'mending': 'mending', 'ngibul': 'ngibul', 'dululah': 'dululah', 'baprilialin': 'baprilialin', 'kpkri': 'kpkri', 'hehhbegoitu': 'hehhbegoitu', 'freeport': 'freeport', 'gimanapertambangan': 'gimanapertambangan', 'diluar': 'luar', 'gimanaikn': 'gimanaikn', 'hutan': 'hutan', 'membengkak': 'bengkak', 'triliunn': 'triliunn', 'instruksi': 'instruksi', 'sepi': 'sepi', 'ragu': 'ragu', 'nanam': 'nanam', 'modal': 'modal', 'bbersama': 'bbersama', 'sukseskan': 'sukses', 'bini': 'bini', 'betul': 'betul', 'merefleksikan': 'refleksi', 'caracara': 'caracara', 'bdengan': 'bdengan', 'luas': 'luas', 'lk': 'lk', 'hektar': 'hektar', 'mentawir': 'mentawir', 'ditargetkan': 'target', 'memproduksi': 'produksi', 'bibit': 'bibit', 'juta': 'juta', 'bsobat': 'bsobat', 'hijau': 'hijau', 'semangat': 'semangat', 'jumatnnsemangat': 'jumatnnsemangat', 'tekad': 'tekad', 'penghijauan': 'hijau', 'jambi': 'jambi', 'transformasi': 'transformasi', 'coba': 'coba', 'istana': 'istana', 'adakan': 'adakan', 'poling': 'poling', 'nnbersediakah': 'nnbersediakah', 'junto': 'junto', 'pns': 'pns', 'bdibangunnya': 'bdibangunnya', 'beritamineral': 'beritamineral', 'optimis': 'optimis', 'bangkitkan': 'bangkit', 'jokowibapakinfrastruktur': 'jokowibapakinfrastruktur', 'pilpres': 'pilpres', 'kpu': 'kpu', 'menghitung': 'hitung', 'suara': 'suara', 'hiruk': 'hiruk', 'pikuk': 'pikuk', 'langkah': 'langkah', 'berkembang': 'kembang', 'bberitamineral': 'bberitamineral', 'meningkat': 'tingkat', 'tinulltinaaa': 'tinulltinaaa', 'memajukan': 'maju', 'nndki': 'nndki', 'nkotaduniauntuksemua': 'nkotaduniauntuksemua', 'megakumalasarie': 'megakumalasarie', 'peringatan': 'ingat', 'hut': 'hut', 'peningkatan': 'tingkat', 'keren': 'keren', 'btiga': 'btiga', 'berjalan': 'jalan', 'lancar': 'lancar', 'kendala': 'kendala', 'mimpi': 'mimpi', 'kecebong': 'kecebong', 'anjing': 'anjing', 'kejauhan': 'jauh', 'gw': 'gw', 'tw': 'tw', 'kl': 'kl', 'pemimpin': 'pimpin', 'cukong': 'cukong', 'nkri': 'nkri', 'rusak': 'rusak', 'menarik': 'tarik', 'dikasih': 'kasih', 'insentif': 'insentif', 'periode': 'periode', 'hguhgb': 'hguhgb', 'dsb': 'dsb', 'itupun': 'itu', 'nandashanum': 'nandashanum', 'bkeren': 'bkeren', 'calon': 'calon', 'bayo': 'bayo', 'oicoffe': 'oicoffe', 'berpotensi': 'potensi', 'bikin': 'bikin', 'teknologi': 'teknologi', 'mantap': 'mantap', 'tuh': 'tuh', 'yuk': 'yuk', 'positifekonomi': 'positifekonomi', 'mensejahterakan': 'sejahtera', 'bindonesia': 'bindonesia', 'positif': 'positif', 'bjiwatertukar': 'bjiwatertukar', 'tingkatkan': 'tingkat', 'bidang': 'bidang', 'boicoffe': 'boicoffe', 'pajakpajak': 'pajakpajak', 'harga': 'harga', 'ambisinya': 'ambisi', 'byusufdumdum': 'byusufdumdum', 'kantor': 'kantor', 'pbnu': 'pbnu', 'diresmikan': 'resmi', 'mendkung': 'mendkung', 'peluang': 'peluang', 'potensi': 'potensi', 'halal': 'halal', 'hub': 'hub', 'hilirisasi': 'hilir', 'proaktif': 'proaktif', 'zelenskyyua': 'zelenskyyua', 'nawarin': 'nawarin', 'tanah': 'tanah', 'npliss': 'npliss', 'impes': 'impes', 'tu': 'tu', 'mai': 'mai', 'kantri': 'kantri', 'terapkan': 'terap', 'depanniknnusantarandukungiknnusantaraniknpemerataanekonomi': 'depanniknnusantarandukungiknnusantaraniknpemerataanekonomi', 'positifterhadap': 'positifterhadap', 'pemerataan': 'perata', 'bawa': 'bawa', 'positifke': 'positifke', 'salam': 'salam', 'bangga': 'bangga', 'matang': 'matang', 'siapkan': 'siap', 'bus': 'bus', 'semoga': 'moga', 'bpapaloren': 'bpapaloren', 'maaf': 'maaf', 'nih': 'nih', 'entar': 'entar', 'ngisi': 'ngisi', 'bahasa': 'bahasa', 'lg': 'lg', 'heuheu': 'heuheu', 'jiwatertukar': 'jiwatertukar', 'akademisi': 'akademisi', 'ikut': 'ikut', 'bkompastv': 'bkompastv', 'elonmusk': 'elonmusk', 'melebihi': 'lebih', 'prastow': 'prastow', 'holiday': 'holiday', 'super': 'super', 'deduction': 'deduction', 'antusiasme': 'antusiasme', 'publik': 'publik', 'pasca': 'pasca', 'market': 'market', 'sounding': 'sounding', 'isi': 'isi', 'berdamaiwaduh': 'berdamaiwaduh', 'malu': 'malu', 'kali': 'kali', 'berdamaimana': 'berdamaimana', 'aq': 'aq', 'yaa': 'yaa', 'munafik': 'munafik', 'bantu': 'bantu', 'kreatif': 'kreatif', 'bconfesstweetmy': 'bconfesstweetmy', 'offshore': 'offshore', 'xpnh': 'xpnh', 'rsnya': 'rsnya', 'kedeng': 'kedeng', 'ngan': 'ngan', 'osea': 'osea', 'rate': 'rate', 'usdday': 'usdday', 'la': 'la', 'bmakin': 'bmakin', 'of': 'of', 'indonesiannsumatera': 'indonesiannsumatera', 'iknnnsulawesi': 'iknnnsulawesi', 'unggulnnsulawesi': 'unggulnnsulawesi', 'tengahnkotaduniauntuksemua': 'tengahnkotaduniauntuksemua', 'bpgi': 'bpgi', 'kukar': 'kukar', 'nusantarannsulawesi': 'nusantarannsulawesi', 'gerakan': 'gera', 'lingkungannnsulawesi': 'lingkungannnsulawesi', 'drpd': 'drpd', 'bayaran': 'bayar', 'mendingan': 'mending', 'terhormat': 'hormat', 'iknnbrg': 'iknnbrg', 'suami': 'suami', 'isteri': 'isteri', 'binfrastruktur': 'binfrastruktur', 'citynnsulawesi': 'citynnsulawesi', 'bentuk': 'bentuk', 'komitmen': 'komitmen', 'berkelanjutan': 'lanjut', 'nnsulawesi': 'nnsulawesi', 'lingkungannnsumatera': 'lingkungannnsumatera', 'sentrisnnsulawesi': 'sentrisnnsulawesi', 'kebanggaan': 'bangga', 'iknnnsumatera': 'iknnnsumatera', 'nusanrtara': 'nusanrtara', 'simbol': 'simbol', 'kerukunan': 'rukun', 'nusantarannsumatera': 'nusantarannsumatera', 'bingung': 'bingung', 'jg': 'jg', 'krna': 'krna', 'musim': 'musim', 'kemarau': 'kemarau', 'bersih': 'bersih', 'magnet': 'magnet', 'pertumbuhan': 'tumbuh', 'usaha': 'usaha', 'bkehadiran': 'bkehadiran', 'bri': 'bri', 'finlandia': 'finlandia', 'kembangkan': 'kembang', 'sepenuhnya': 'sepenuh', 'kawal': 'kawal', 'citynnsumatera': 'citynnsumatera', 'mahasiswa': 'mahasiswa', 'citynkotaduniauntuksemua': 'citynkotaduniauntuksemua', 'nusantaranndki': 'nusantaranndki', 'mengangkat': 'angkat', 'kearifan': 'arif', 'bpddk': 'bpddk', 'positifnndki': 'positifnndki', 'pariwisata': 'pariwisata', 'pakar': 'pakar', 'bertahap': 'tahap', 'melibatkan': 'libat', 'binilah': 'bini', 'bkereennikn': 'bkereennikn', 'btargetnya': 'btargetnya', 'bzarazettirazr': 'bzarazettirazr', 'sales': 'sales', 'kalik': 'kalik', 'lingkungan': 'lingkung', 'disana': 'sana', 'udaranya': 'udara', 'segar': 'segar', 'sehat': 'sehat', 'bmanfaat': 'bmanfaat', 'mengembangkan': 'kembang', 'bhaktirah': 'bhaktirah', 'mbaksri': 'mbaksri', 'apapun': 'apa', 'tuntutannya': 'tuntut', 'mundur': 'mundur', 'knpagar': 'knpagar', 'batal': 'batal', 'terealisasi': 'realisasi', 'bhey': 'bhey', 'rokok': 'rokok', 'dongs': 'dongs', 'respect': 'respect', 'legend': 'legend', 'banyaknya': 'banyak', 'riang': 'riang', 'terbuka': 'buka', 'masyarakatkotaduniauntuksemua': 'masyarakatkotaduniauntuksemua', 'hebatkotaduniauntuksemua': 'hebatkotaduniauntuksemua', 'nusantarakotaduniauntuksemua': 'nusantarakotaduniauntuksemua', 'majukan': 'maju', 'indonesiakotaduniauntuksemua': 'indonesiakotaduniauntuksemua', 'dimata': 'mata', 'rakyatkotaduniauntuksemua': 'rakyatkotaduniauntuksemua', 'perencanaan': 'rencana', 'majukotaduniauntuksemua': 'majukotaduniauntuksemua', 'balshaibashihab': 'balshaibashihab', 'duitnya': 'duit', 'bangunn': 'bangunn', 'binfo': 'binfo', 'citynnaceh': 'citynnaceh', 'bmbaksri': 'bmbaksri', 'iknnnaceh': 'iknnnaceh', 'direncanakan': 'rencana', 'diputuskan': 'putus', 'rinnaceh': 'rinnaceh', 'bwaw': 'bwaw', 'wapres': 'wapres', 'temui': 'temu', 'bos': 'bos', 'maruf': 'maruf', 'diklaim': 'klaim', 'percepat': 'cepat', 'alasan': 'alas', 'golkar': 'golkar', 'airlangga': 'airlangga', 'hartarto': 'hartarto', 'duta': 'duta', 'pemuda': 'pemuda', 'sadar': 'sadar', 'hukum': 'hukum', 'ilmu': 'ilmu', 'budaya': 'budaya', 'songsong': 'songsong', 'iknndihuni': 'iknndihuni', 'sukses': 'sukses', 'raksasa': 'raksasa', 'properti': 'properti', 'lirik': 'lirik', 'itb': 'itb', 'jalin': 'jalin', 'kesepakatan': 'sepakat', 'digitalisasi': 'digitalisasi', 'komposisi': 'komposisi', 'capai': 'capai', 'men': 'men', 'btancap': 'btancap', 'gas': 'gas', 'bandinilayla': 'bandinilayla', 'bnews': 'bnews', 'bginaoktorina': 'bginaoktorina', 'positifpada': 'positifpada', 'kelompok': 'kelompok', 'heran': 'heran', 'kotaku': 'kota', 'berkonsepkan': 'konsep', 'bkingparatha': 'bkingparatha', 'gorontalo': 'gorontalo', 'harus': 'harus', 'bkonsep': 'bkonsep', 'terbaik': 'baik', 'didunia': 'dunia', 'aminin': 'aminin', 'sepaku': 'paku', 'pengamanan': 'aman', 'meninjau': 'tinjau', 'hanya': 'hanya', 'mengalami': 'alami', 'pesat': 'pesat', 'perekonomiannnikn': 'perekonomiannnikn', 'bjagat': 'bjagat', 'sadarlah': 'sadar', 'indonesiatdk': 'indonesiatdk', 'tuk': 'tuk', 'berdiam': 'diam', 'diriharus': 'diriharus', 'bersatu': 'satu', 'tolak': 'tolak', 'omnibuslaw': 'omnibuslaw', 'hip': 'hip', 'iknuu': 'iknuu', 'sensasi': 'sensasi', 'alam': 'alam', 'citynnikn': 'citynnikn', 'bdaya': 'bdaya', 'tampung': 'tampung', 'tpa': 'tpa', 'manggar': 'manggar', 'bgorontalo': 'bgorontalo', 'bagus': 'bagus', 'citacita': 'citacita', 'unggulnnikn': 'unggulnnikn', 'sabar': 'sabar', 'menunggu': 'tunggu', 'bsemoga': 'bsemoga', 'riau': 'riau', 'bhalo': 'bhalo', 'sobatkomibu': 'sobatkomibu', 'memasuki': 'pasuk', 'tahap': 'tahap', 'lhonnapa': 'lhonnapa', 'diterima': 'terima', 'harusnya': 'harus', 'uni': 'uni', 'barangkali': 'barangkali', 'penawaran': 'tawar', 'nyoba': 'nyoba', 'expansi': 'expansi', 'australia': 'australia', 'bnyatanya': 'bnyatanya', 'musk': 'musk', 'suka': 'suka', 'beli': 'beli', 'iknnpadahal': 'iknnpadahal', 'mahalninvestor': 'mahalninvestor', 'doakan': 'doa', 'bmantap': 'bmantap', 'iknnnikn': 'iknnnikn', 'futur': 'futur', 'bjumlah': 'bjumlah', 'pengembang': 'kembang', 'bnusa': 'bnusa', 'tenggara': 'tenggara', 'timurnikn': 'timurnikn', 'merepresentasikan': 'representasi', 'majunnikn': 'majunnikn', 'rajaandalas': 'rajaandalas', 'pgi': 'pgi', 'iknnkepulauan': 'iknnkepulauan', 'bangka': 'bangka', 'majunkepulauan': 'majunkepulauan', 'usharanimuni': 'usharanimuni', 'kawan': 'kawan', 'nusantarankepulauan': 'nusantarankepulauan', 'bmari': 'bmari', 'torang': 'torang', 'didukung': 'dukung', 'bmantapntiga': 'bmantapntiga', 'unggulnkepulauan': 'unggulnkepulauan', 'paknnikn': 'paknnikn', 'berkat': 'berkat', 'sejahterakan': 'sejahtera', 'indonesiankepulauan': 'indonesiankepulauan', 'bjika': 'bjika', 'president': 'president', 'merasakakan': 'merasakakan', 'kesusahan': 'susah', 'penderitaan': 'derita', 'sebaiknya': 'baik', 'lingkungannnikn': 'lingkungannnikn', 'kutai': 'kuta', 'kartanegara': 'kartanegara', 'btarget': 'btarget', 'diperoleh': 'oleh', 'bbentuk': 'bbentuk', 'merataverse': 'merataverse', 'btetap': 'btetap', 'aspek': 'aspek', 'poin': 'poin', 'kontrol': 'kontrol', 'ditinggalkan': 'tinggal', 'pantesan': 'pantesan', 'bdukungan': 'bdukungan', 'tap': 'tap', 'disematkan': 'semat', 'btorng': 'btorng', 'tergetkan': 'tergetkan', 'daerah': 'daerah', 'penopang': 'topang', 'bmerepresentasikan': 'bmerepresentasikan', 'unggul': 'unggul', 'wujud': 'wujud', 'bibu': 'bibu', 'jati': 'jati', 'indonesiannsulawesi': 'indonesiannsulawesi', 'bwahh': 'bwahh', 'nusantarannwarganet': 'nusantarannwarganet', 'bada': 'bada', 'data': 'data', 'ditutupisebaiknya': 'ditutupisebaiknya', 'dibuka': 'buka', 'carut': 'carut', 'marutnya': 'marut', 'pengelolaan': 'kelola', 'masuknya': 'masuk', 'membantu': 'bantu', 'arsjadrasjid': 'arsjadrasjid', 'iknnusantara': 'iknnusantara', 'inklusifkolaboratif': 'inklusifkolaboratif', 'menyambut': 'sambut', 'bpoeamran': 'bpoeamran', 'realisasi': 'realisasi', 'emang': 'emang', 'memenuhi': 'penuh', 'target': 'target', 'bong': 'bong', 'lingkungannnwarganet': 'lingkungannnwarganet', 'indonesianikn': 'indonesianikn', 'nusantaran': 'nusantaran', 'nikn': 'nikn', 'citynnwarganet': 'citynnwarganet', 'bprogres': 'bprogres', 'bsukseskan': 'bsukseskan', 'terbukti': 'bukti', 'bkeuangannewsid': 'bkeuangannewsid', 'musti': 'musti', 'ngutus': 'ngutus', 'prabowo': 'prabowo', 'sederhana': 'sederhana', 'ketemu': 'ketemu', 'membanggakan': 'bangga', 'pembanguna': 'pembanguna', 'bmantaap': 'bmantaap', 'buntuk': 'buntuk', 'perkembangan': 'kembang', 'bkita': 'bkita', 'tuntas': 'tuntas', 'perekenomian': 'perekenomian', 'sentris': 'sentris', 'pemerintahan': 'perintah', 'penandatangan': 'penandatangan', 'kontraktor': 'kontraktor', 'perolehan': 'oleh', 'nilai': 'nilai', 'buppdate': 'buppdate', 'drun': 'drun', 'targetnya': 'target', 'doang': 'doang', 'salmakiandra': 'salmakiandra', 'giginpraginanto': 'giginpraginanto', 'akar': 'akar', 'rumput': 'rumput', 'no': 'no', 'way': 'way', 'bbangnalar': 'bbangnalar', 'mngkinmreka': 'mngkinmreka', 'iknprcpat': 'iknprcpat', 'boneka': 'boneka', 'mamarika': 'mamarika', 'bngung': 'bngung', 'demonya': 'demo', 'bkorban': 'bkorban', 'iknnudah': 'iknnudah', 'kerasa': 'rasa', 'hawa': 'hawa', 'gerahnya': 'gerah', 'cooy': 'cooy', 'panasgile': 'panasgile', 'menawarkan': 'tawar', 'senin': 'senin', 'naik': 'naik', 'brakyat': 'brakyat', 'kejayaan': 'jaya', 'bwah': 'bwah', 'surodilagan': 'surodilagan', 'democrazymedia': 'democrazymedia', 'gedunggedung': 'gedunggedung', 'swasta': 'swasta', 'januari': 'januari', 'pemesan': 'mes', 'ngributin': 'ngributin', 'formulasmntr': 'formulasmntr', 'nombok': 'nombok', 'trilyunan': 'trilyunan', 'laporan': 'lapor', 'dr': 'dr', 'mandalika': 'mandalika', 'nusa': 'nusa', 'timurnpemindahan': 'timurnpemindahan', 'harapan': 'harap', 'bospurwa': 'bospurwa', 'silakan': 'sila', 'simak': 'simak', 'video': 'video', 'inindulu': 'inindulu', 'esemka': 'esemka', 'beda': 'beda', 'tipis': 'tipis', 'tukang': 'tukang', 'obat': 'obat', 'pinggir': 'pinggir', 'elinaazkia': 'elinaazkia', 'banget': 'banget', 'curiga': 'curiga', 'bengkakpuas': 'bengkakpuas', 'lingkungannndaerah': 'lingkungannndaerah', 'istimewa': 'istimewa', 'iknnndaerah': 'iknnndaerah', 'indonesianndaerah': 'indonesianndaerah', 'bdalam': 'bdalam', 'pertemuan': 'temu', 'menpora': 'menpora', 'zainudin': 'zainudin', 'amali': 'amal', 'melaporkan': 'lapor', 'kementerian': 'menteri', 'representasu': 'representasu', 'unggulnndaerah': 'unggulnndaerah', 'desain': 'desain', 'citynndaerah': 'citynndaerah', 'keuarkan': 'uar', 'bkmi': 'bkmi', 'dewan': 'dewan', 'adat': 'adat', 'dayak': 'dayak', 'cbg': 'cbg', 'barat': 'barat', 'pemb': 'pemb', 'kmi': 'kmi', 'tdk': 'tdk', 'prnah': 'prnah', 'mmnta': 'mmnta', 'dpndhkan': 'dpndhkan', 'bsuruh': 'bsuruh', 'daracega': 'daracega', 'nnbiar': 'nnbiar', 'produk': 'produk', 'unggulan': 'unggul', 'bdan': 'bdan', 'mala': 'mala', 'sibuk': 'sibuk', 'ditengah': 'tengah', 'rakyatnya': 'rakyat', 'masuk': 'masuk', 'syurga': 'syurga', 'pintu': 'pintu', 'ojiyuu': 'ojiyuu', 'ingin': 'ingin', 'butuh': 'butuh', 'roket': 'roket', 'tulisan': 'tulis', 'ranisudibyo': 'ranisudibyo', 'besarbesarannnmenurut': 'besarbesarannnmenurut', 'bambang': 'bambang', 'kepala': 'kepala', 'bsegera': 'bsegera', 'bursa': 'bursa', 'bsbk': 'bsbk', 'tangkap': 'tangkap', 'bisnis': 'bisnis', 'terbaru': 'baru', 'kaukutangkap': 'tangkap', 'susantono': 'susantono', 'fisik': 'fisik', 'besarbesaran': 'besarbesaran', 'nidyaluna': 'nidyaluna', 'nnpersiapan': 'nnpersiapan', 'dilakukam': 'dilakukam', 'besarbesaean': 'besarbesaean', 'geloraco': 'geloraco', 'bnandashanum': 'bnandashanum', 'suciranii': 'suciranii', 'momentum': 'momentum', 'pembangunanikn': 'pembangunanikn', 'bbalikpapan': 'bbalikpapan', 'dhahana': 'dhahana', 'putra': 'putra', 'plt': 'plt', 'pp': 'pp', 'didampingi': 'damping', 'cahyani': 'cahyani', 'suryandari': 'suryandari', 'dir': 'dir', 'perancangan': 'ancang', 'peraturan': 'atur', 'infrastructure': 'infrastructure', 'metropolis': 'metropolis', 'tujuannya': 'tuju', 'ngundang': 'ngundang', 'ribuan': 'ribu', 'desa': 'desa', 'pake': 'pake', 'duit': 'duit', 'pribadi': 'pribadi', 'nkan': 'nkan', 'triliun': 'triliun', 'ticket': 'ticket', 'akomodasi': 'akomodasi', 'bhermawandevina': 'bhermawandevina', 'milih': 'milih', 'ngeluarin': 'ngeluarin', 'ketimbang': 'ketimbang', 'stabilisasi': 'stabilisasi', 'ea': 'ea', 'tembus': 'tembus', 'rupiah': 'rupiah', 'terpuruk': 'puruk', 'nangan': 'nang', 'angannya': 'angan', 'nkantrok': 'nkantrok', 'nera': 'nera', 'habibie': 'habibie', 'belasan': 'bas', 'tercermin': 'cermin', 'baspek': 'baspek', 'syukur': 'syukur', 'jgjadiklonya': 'jgjadiklonya', 'ntar': 'ntar', 'disuruh': 'suruh', 'loo': 'loo', 'setuju': 'tuju', 'fi': 'fi', 'dilanjutkan': 'lanjut', 'byang': 'byang', 'bkepulauan': 'bkepulauan', 'belitung': 'belitung', 'byogisaputrahd': 'byogisaputrahd', 'nusantaranndaerah': 'nusantaranndaerah', 'yogyakartanikn': 'yogyakartanikn', 'umkmnkepulauan': 'umkmnkepulauan', 'bmedsossamson': 'bmedsossamson', 'terbaiknndaerah': 'terbaiknndaerah', 'bmengintip': 'bmengintip', 'positifnndaerah': 'positifnndaerah', 'bukti': 'bukti', 'bkota': 'bkota', 'kek': 'kek', 'urgensinya': 'urgensi', 'jalur': 'jalur', 'kuat': 'kuat', 'tonggak': 'tonggak', 'majunndaerah': 'majunndaerah', 'hebatnndaerah': 'hebatnndaerah', 'indonesianpapua': 'indonesianpapua', 'bertahapnpapua': 'bertahapnpapua', 'briau': 'briau', 'support': 'support', 'lingkungannpapua': 'lingkungannpapua', 'bsahabatpp': 'bsahabatpp', 'beriringan': 'iring', 'menguntungkan': 'untung', 'membeli': 'beli', 'bro': 'bro', 'karna': 'karna', 'omset': 'omset', 'perbulan': 'bulan', 'jayanndaerah': 'jayanndaerah', 'bsejumlah': 'bsejumlah', 'bduta': 'bduta', 'mengganggu': 'ganggu', 'nsumatera': 'nsumatera', 'teknogav': 'teknogav', 'sajikan': 'saji', 'virtual': 'virtual', 'terhubung': 'hubung', 'bbersiaplah': 'bbersiaplah', 'citynsumatera': 'citynsumatera', 'hidupkan': 'hidup', 'bmasyarkat': 'bmasyarkat', 'bjoss': 'bjoss', 'jaga': 'jaga', 'bsemua': 'bsemua', 'terkena': 'kena', 'positifpembangunan': 'positifpembangunan', 'nvroost': 'nvroost', 'kalangan': 'kalang', 'nusnatara': 'nusnatara', 'an': 'an', 'positifnkepulauan': 'positifnkepulauan', 'mandaat': 'mandaat', 'bmantab': 'bmantab', 'platmirah': 'platmirah', 'menghuni': 'huni', 'nusantarankotaduniauntuksemua': 'nusantarankotaduniauntuksemua', 'anakn': 'anakn', 'cerdas': 'cerdas', 'bbambang': 'bbambang', 'menyebut': 'sebut', 'strategi': 'strategi', 'bmembanggakan': 'bmembanggakan', 'citynkepulauan': 'citynkepulauan', 'bhantamanhitam': 'bhantamanhitam', 'solusi': 'solusi', 'damai': 'damai', 'populasi': 'populasi', 'berteknologi': 'teknologi', 'canggihnkepulauan': 'canggihnkepulauan', 'bresesi': 'bresesi', 'niknat': 'niknat', 'dustakan': 'dusta', 'bburnoxyz': 'bburnoxyz', 'perlindungan': 'lindung', 'sosial': 'sosial', 'rapbn': 'rapbn', 'nominalnyanaik': 'nominalnyanaik', 'bjokoei': 'bjokoei', 'iknnnkalimantan': 'iknnnkalimantan', 'bnaomisusantiiii': 'bnaomisusantiiii', 'pengen': 'ken', 'ndukungiknnusantara': 'ndukungiknnusantara', 'lingkungannnkalimantan': 'lingkungannnkalimantan', 'identitas': 'identitas', 'indonesiannkalimantan': 'indonesiannkalimantan', 'berpengaruh': 'pengaruh', 'arab': 'arab', 'papua': 'papua', 'bdari': 'bdari', 'saudi': 'saudi', 'berpeluang': 'peluang', 'mendapatkan': 'dapat', 'menopang': 'topang', 'kebutuhan': 'butuh', 'kana': 'kana', 'bmasuknya': 'bmasuknya', 'maluku': 'malu', 'bhadirnya': 'bhadirnya', 'delegasi': 'delegasi', 'berinvenstasi': 'berinvenstasi', 'bpada': 'bpada', 'memiliki': 'milik', 'menghadiri': 'hadir', 'konferensi': 'konferensi', 'bterbaik': 'bterbaik', 'bhubungan': 'bhubungan', 'dipertahankan': 'tahan', 'presentasi': 'presentasi', 'bajakan': 'baja', 'bketika': 'bketika', 'rayu': 'rayu', 'sultan': 'sultan', 'jajak': 'jajak', 'pasar': 'pasar', 'bjangan': 'bjangan', 'pastikan': 'pasti', 'keamanan': 'aman', 'si': 'si', 'ber': 'ber', 'ktt': 'ktt', 'selamat': 'selamat', 'pm': 'pm', 'inggris': 'inggris', 'bktt': 'bktt', 'dinilai': 'nilai', 'bdeklarasi': 'bdeklarasi', 'menteri': 'menteri', 'digital': 'digital', 'demm': 'demm', 'bpersatuan': 'bpersatuan', 'insinyur': 'insinyur', 'menginisialisasi': 'inisial', 'terbentuknya': 'bentuk', 'bsiapa': 'bsiapa', 'peserta': 'serta', 'recovertogetherrecoverstronger': 'recovertogetherrecoverstronger', 'aviation': 'aviation', 'dialogue': 'dialogue', 'hasilkan': 'hasil', 'prioritas': 'prioritas', 'brevitalisasi': 'brevitalisasi', 'tmii': 'tmii', 'persiapan': 'siap', 'presidensi': 'presidensi', 'nusantarannmalut': 'nusantarannmalut', 'bsukses': 'bsukses', 'masbronnu': 'masbronnu', 'bkepala': 'bkepala', 'bhebat': 'bhebat', 'infrastrukturn': 'infrastrukturn', 'nnmalut': 'nnmalut', 'tni': 'tni', 'polri': 'polri', 'lingkungannnmalut': 'lingkungannnmalut', 'timurnkomitmen': 'timurnkomitmen', 'ulama': 'ulama', 'malut': 'malut', 'bsambutan': 'bsambutan', 'oktober': 'oktober', 'youtube': 'youtube', 'cukup': 'cukup', 'baiknnibu': 'baiknnibu', 'dikotori': 'kotor', 'abuwaras': 'abuwaras', 'voc': 'voc', 'menikmati': 'nikmat', 'batavia': 'batavia', 'tahunnnkeprok': 'tahunnnkeprok', 'barudak': 'barudak', 'sindaisalie': 'sindaisalie', 'kelestarian': 'lestari', 'nnyg': 'nnyg', 'menentang': 'tentang', 'bgenerasi': 'bgenerasi', 'muda': 'muda', 'terwujudnya': 'wujud', 'hadirnya': 'hadir', 'ntapi': 'ntapi', 'nyinyir': 'nyinyir', 'suku': 'suku', 'dihina': 'hina', 'tp': 'tp', 'terang': 'terang', 'ngak': 'ngak', 'tunda': 'tunda', 'kah': 'kah', 'asboedionoid': 'asboedionoid', 'prestasi': 'prestasi', 'dibanggakan': 'bangga', 'semesta': 'semesta', 'nasib': 'nasib', 'dialami': 'alami', 'catatankaqihati': 'catatankaqihati', 'nsampai': 'nsampai', 'masuki': 'masuk', 'tahapan': 'tahap', 'land': 'land', 'wuiih': 'wuiih', 'anggarkan': 'anggar', 'hampir': 'hampir', 'mnjasa': 'mnjasa', 'konsultansi': 'konsultansi', 'anidraayt': 'anidraayt', 'bpn': 'bpn', 'bcatatankaqihati': 'bcatatankaqihati', 'galerifitri': 'galerifitri', 'tahapndan': 'tahapndan', 'dlm': 'dlm', 'pembersihan': 'bersih', 'bkerukunan': 'bkerukunan', 'etnis': 'etnis', 'batak': 'batak', 'karo': 'karo', 'simalem': 'simalem', 'bontang': 'bontang', 'adl': 'adl', 'sulit': 'sulit', 'dibantah': 'ban', 'bhw': 'bhw', 'berniat': 'niat', 'raja': 'raja', 'nnngga': 'nnngga', 'bforjakeu': 'bforjakeu', 'joss': 'joss', 'forjakeu': 'forjakeu', 'ditinjau': 'tinjau', 'nusantarannpresiden': 'nusantarannpresiden', 'ae': 'ae', 'nek': 'nek', 'rumitikn': 'rumitikn', 'noviroose': 'noviroose', 'pemkab': 'pemkab', 'iknnndiskominfo': 'iknnndiskominfo', 'kabupaten': 'kabupaten', 'dafip': 'dafip', 'haryanto': 'haryanto', 'kemenpu': 'kemenpu', 'halo': 'halo', 'sahabatpupr': 'sahabatpupr', 'dinas': 'dinas', 'kominfo': 'kominfo', 'bkadrun': 'bkadrun', 'takut': 'takut', 'dayakmakanya': 'dayakmakanya', 'bmwlorg': 'bmwlorg', 'promosiin': 'promosiin', 'tarik': 'tarik', 'tahunmantappp': 'tahunmantappp', 'bkotanusantara': 'bkotanusantara', 'akornas': 'akornas', 'pemerataaan': 'pemerataaan', 'alisyarief': 'alisyarief', 'teenangjanuari': 'teenangjanuari', 'gedung': 'gedung', 'dah': 'dah', 'nampak': 'nampak', 'kotanusantara': 'kotanusantara', 'derap': 'derap', 'semangatnusantara': 'semangatnusantara', 'bkalimantan': 'bkalimantan', 'helmifelis': 'helmifelis', 'gaakan': 'gaakan', 'laku': 'laku', 'kangakuy': 'kangakuy', 'kacep': 'kacep', 'jktbdgcoret': 'jktbdgcoret', 'stop': 'stop', 'pemilupilkada': 'pemilupilkada', 'on': 'on', 'schedule': 'schedule', 'sesuai': 'sesuai', 'amanat': 'amanat', 'uunsetelah': 'uunsetelah', 'bteddgus': 'bteddgus', 'urgennmisal': 'urgennmisal', 'golkarpedia': 'golkarpedia', 'hetifah': 'hetifah', 'penguatan': 'kuat', 'sdm': 'sdm', 'oongroni': 'oongroni', 'nenek': 'nenek', 'lampir': 'lampir', 'ngebacotkemarin': 'ngebacotkemarin', 'ribut': 'ribut', 'ijazah': 'ijazah', 'ketahuan': 'tahu', 'bohong': 'bohong', 'cuitan': 'cuit', 'hapus': 'hapus', 'ngebacot': 'ngebacot', 'dakhnan': 'dakhnan', 'burhanmuhtadi': 'burhanmuhtadi', 'yunartowijaya': 'yunartowijaya', 'saifulmujani': 'saifulmujani', 'dppnasdem': 'dppnasdem', 'pdiperjuangan': 'pdiperjuangan', 'model': 'model', 'perpolitikan': 'politik', 'haji': 'haji', 'gunakan': 'guna', 'haranamardjihad': 'haranamardjihad', 'habiskan': 'habis', 'hutang': 'hutang', 'sepatutnya': 'patut', 'kades': 'kades', 'bdoktertifa': 'bdoktertifa', 'ghaib': 'ghaib', 'oligarki': 'oligarki', 'reformasi': 'reformasi', 'berlanjut': 'lanjut', 'aburojoo': 'aburojoo', 'lha': 'lha', 'trus': 'trus', 'ngapainnapa': 'ngapainnapa', 'dsruh': 'dsruh', 'bkin': 'bkin', 'tenan': 'tenan', 'iinasurbakti': 'iinasurbakti', 'iknnsigapmembangunnegeri': 'iknnsigapmembangunnegeri', 'lanjooot': 'lanjooot', 'terjunnya': 'terjun', 'wisata': 'wisata', 'doadoa': 'doadoa', 'terlibat': 'libat', 'lindungan': 'lindung', 'allah': 'allah', 'swt': 'swt', 'enam': 'enam', 'seindonesia': 'indonesia', 'kunjungi': 'kunjung', 'bkitaadlidn': 'bkitaadlidn', 'kadal': 'kadal', 'otaknya': 'otak', 'sampe': 'sampe', 'kesinicoba': 'kesinicoba', 'palestina': 'palestina', 'semuakadal': 'semuakadal', 'bvivacoid': 'bvivacoid', 'seharusnyari': 'seharusnyari', 'tuan': 'tuan', 'penyelenggaraan': 'selenggara', 'dg': 'dg', 'balisyarief': 'balisyarief', 'katanyapunya': 'katanyapunya', 'subsidi': 'subsidi', 'dicabut': 'cabut', 'nyatanyancuma': 'nyatanyancuma', 'nafsu': 'nafsu', 'bfinlandia': 'bfinlandia', 'berminat': 'minat', 'versi': 'versi', 'virtualniknnusantarandukungiknnusantaraniknsejahterakanindonesia': 'virtualniknnusantarandukungiknnusantaraniknsejahterakanindonesia', 'polhuk': 'polhuk', 'dumeh': 'dumeh', 'opo': 'opo', 'guna': 'guna', 'lgsg': 'lgsg', 'kelar': 'kelar', 'candi': 'candi', 'prambanan': 'prambanan', 'bberbagai': 'bberbagai', 'bsutanmangara': 'bsutanmangara', 'pemberitaan': 'berita', 'napa': 'napa', 'nsedangkan': 'nsedangkan', 'imcmushroom': 'imcmushroom', 'mikir': 'mikir', 'nbuat': 'nbuat', 'manfaatnyanbanyak': 'manfaatnyanbanyak', 'kelaparanemangnya': 'kelaparanemangnya', 'pergi': 'pergi', 'kesana': 'kesana', 'hidayatnatari': 'hidayatnatari', 'dananya': 'dana', 'mananduitnya': 'mananduitnya', 'mananmemangnya': 'mananmemangnya', 'perjalanan': 'jalan', 'rumit': 'rumit', 'ataurumit': 'ataurumit', 'rumitkan': 'rumit', 'knp': 'knp', 'justrupaksakan': 'justrupaksakan', 'antaranews': 'antaranews', 'dijadwalkan': 'jadwal', 'national': 'national', 'capital': 'capital', 'bsabut': 'bsabut', 'patuhprokesselalusehat': 'patuhprokesselalusehat', 'kunjungan': 'kunjung', 'bseandainya': 'bseandainya', 'ngibulnnmau': 'ngibulnnmau', 'pulau': 'pulau', 'ane': 'ane', 'dukungnnkloperlu': 'dukungnnkloperlu', 'nusakambangan': 'nusakambangan', 'jadiin': 'jadiin', 'pemanis': 'man', 'diskon': 'diskon', 'bnichosilalahi': 'bnichosilalahi', 'bergerak': 'gerak', 'keras': 'keras', 'dijual': 'jual', 'cina': 'cina', 'rezim': 'rezim', 'olgarki': 'olgarki', 'ms': 'ms', 'agusyudhoyono': 'agusyudhoyono', 'meeting': 'meeting', 'bongnkelas': 'bongnkelas', 'pencitraan': 'citra', 'wakil': 'wakil', 'bleonitalestari': 'bleonitalestari', 'ilustrasinya': 'ilustrasi', 'sepatu': 'sepatu', 'kulit': 'kulit', 'bryawiedy': 'bryawiedy', 'peduli': 'peduli', 'ngutang': 'ngutang', 'ngemis': 'ngemis', 'gadaikan': 'gadai', 'walapun': 'walapun', 'susah': 'susah', 'bsekalian': 'bsekalian', 'toll': 'toll', 'dihentikan': 'henti', 'keyword': 'keyword', 'penghematan': 'hemat', 'penasehat': 'nasehat', 'tony': 'tony', 'blair': 'blair', 'terkuat': 'kuat', 'duniannsehun': 'duniannsehun', 'jt': 'jt', 'merdeka': 'merdeka', 'timurncakwmenlanyallaacademynnibukotanegara': 'timurncakwmenlanyallaacademynnibukotanegara', 'timurnindiaknowledgeniknidnnibukotanegara': 'timurnindiaknowledgeniknidnnibukotanegara', 'bderap': 'bderap', 'nusantarannalarininstituteniknnusantaraidnnibukotanegara': 'nusantarannalarininstituteniknnusantaraidnnibukotanegara', 'emas': 'emas', 'nusantaranfordamailnceriaceritakitannibukotanegara': 'nusantaranfordamailnceriaceritakitannibukotanegara', 'bstevaniehuangg': 'bstevaniehuangg', 'alhamdulillahnsemoga': 'alhamdulillahnsemoga', 'keluarganya': 'keluarga', 'iknjangan': 'iknjangan', 'bpipri': 'bpipri', 'kemenkopmk': 'kemenkopmk', 'getol': 'getol', 'nibukotanegaraniknnsemangatnusantara': 'nibukotanegaraniknnsemangatnusantara', 'selasa': 'selasa', 'dijamin': 'jamin', 'bahagia': 'bahagia', 'dng': 'dng', 'tergantung': 'gantung', 'menekan': 'tekan', 'senilai': 'nila', 'biki': 'bik', 'gabisa': 'gabisa', 'pecah': 'pecah', 'dadi': 'dadi', 'sumatra': 'sumatra', 'bali': 'bal', 'riegosee': 'riegosee', 'keberadaan': 'ada', 'penandatanganan': 'penandatanganan', 'ngerokok': 'ngerokok', 'pagiii': 'pagiii', 'btokoh': 'btokoh', 'agama': 'agama', 'indon': 'indon', 'dukunikn': 'dukunikn', 'hafalmengingat': 'hafalmengingat', 'isis': 'isis', 'serbaguna': 'serbaguna', 'terrorist': 'terrorist', 'awangawang': 'awangawang', 'membumikan': 'bumi', 'superhub': 'superhub', 'klaster': 'klaster', 'penopangnyanklaster': 'penopangnyanklaster', 'bersihnklaster': 'bersihnklaster', 'farmasi': 'farmasi', 'keluarga': 'keluarga', 'bgalerifitri': 'bgalerifitri', 'brizkidwika': 'brizkidwika', 'nf': 'nf', 'cabang': 'cabang', 'matamu': 'mata', 'picek': 'picek', 'brinindonesia': 'brinindonesia', 'bpupr': 'bpupr', 'dkijakarta': 'dkijakarta', 'sepeda': 'sepeda', 'diperuntukkan': 'untuk', 'melanda': 'landa', 'wajib': 'wajib', 'bpt': 'bpt', 'raih': 'raih', 'terima': 'terima', 'nmenpora': 'nmenpora', 'bpemkab': 'bpemkab', 'bkalo': 'bkalo', 'perencana': 'rencana', 'rebutan': 'rebut', 'kue': 'kue', 'rahasia': 'rahasia', 'mateng': 'mateng', 'centra': 'centra', 'ngab': 'ngab', 'roselasetia': 'roselasetia', 'peluncuran': 'luncur', 'doankwarto': 'doankwarto', 'mahal': 'mahal', 'iknnnternyata': 'iknnnternyata', 'penanganan': 'tangan', 'indonselalu': 'indonselalu', 'terdepan': 'depan', 'iblis': 'iblis', 'blis': 'blis', 'dandhylaksono': 'dandhylaksono', 'gampang': 'gampang', 'stadion': 'stadion', 'standar': 'standar', 'fifa': 'fifa', 'sirkuit': 'sirkuit', 'balap': 'balap', 'premiumnnlalu': 'premiumnnlalu', 'afrizamunaf': 'afrizamunaf', 'tngkl': 'tngkl', 'berterima': 'terima', 'jokowihebat': 'jokowihebat', 'polresta': 'polresta', 'balam': 'balam', 'suwandaben': 'suwandaben', 'iknnpromotornya': 'iknnpromotornya', 'ketua': 'ketua', 'dpp': 'dpp', 'apdesi': 'apdesi', 'surtawijayannjokowi': 'surtawijayannjokowi', 'bditinjau': 'bditinjau', 'th': 'th', 'tifa': 'tifa', 'tidur': 'tidur', 'nyenyak': 'nyenyak', 'pakde': 'pakde', 'top': 'top', 'baikarif': 'baikarif', 'hariankompas': 'hariankompas', 'spt': 'spt', 'pd': 'pd', 'fokus': 'fokus', 'cpt': 'cpt', 'bsindaisalie': 'bsindaisalie', 'jatah': 'jatah', 'makax': 'makax', 'bulux': 'bulux', 'diatas': 'atas', 'rencanakan': 'rencana', 'datangkan': 'datang', 'melegetimasi': 'melegetimasi', 'bwh': 'bwh', 'bimcmushroom': 'bimcmushroom', 'puas': 'puas', 'mengiklankan': 'iklan', 'media': 'media', 'karnamungkin': 'karnamungkin', 'kedatangan': 'datang', 'bya': 'bya', 'mimpin': 'mimpin', 'sekarangnnanti': 'sekarangnnanti', 'anis': 'anis', 'presidentnstop': 'presidentnstop', 'kompromi': 'kompromi', 'naudit': 'naudit', 'muhammadsaewad': 'muhammadsaewad', 'garagara': 'garagara', 'babuwaras': 'babuwaras', 'gorila': 'gorila', 'bicara': 'bicara', 'ngerti': 'ngerti', 'bkejaksaan': 'bkejaksaan', 'dokter': 'dokter', 'iknn': 'iknn', 'ntt': 'ntt', 'pendukung': 'dukung', 'buzzerp': 'buzzerp', 'senyap': 'senyap', 'urusan': 'urus', 'bherrikusnadi': 'bherrikusnadi', 'ucapkan': 'ucap', 'kebohongan': 'bohong', 'jgn': 'jgn', 'bebrbasis': 'bebrbasis', 'fakta': 'fakta', 'bhelmifelis': 'bhelmifelis', 'mukidi': 'mukidi', 'wafatpun': 'wafat', 'adajadi': 'adajadi', 'ngandeng': 'ngandeng', 'kejaksaannkementerian': 'kejaksaannkementerian', 'puprn': 'puprn', 'pantau': 'pantau', 'speedtrap': 'speedtrap', 'milik': 'milik', 'kafir': 'kafir', 'main': 'main', 'tl': 'tl', 'keadilan': 'adil', 'berbangsa': 'bangsa', 'biayanya': 'biaya', 'indonesiannikn': 'indonesiannikn', 'kehilangan': 'hilang', 'cucu': 'cucu', 'terampas': 'ampas', 'krisis': 'krisis', 'biknid': 'biknid', 'bnawaninik': 'bnawaninik', 'ronialkhoir': 'ronialkhoir', 'chusnulch': 'chusnulch', 'faktakonsep': 'faktakonsep', 'banjir': 'banjir', 'sponge': 'sponge', 'lu': 'lu', 'qontol': 'qontol', 'keuntungannya': 'untung', 'kemana': 'mana', 'semudah': 'mudah', 'dibayangkan': 'bayang', 'ad': 'ad', 'al': 'al', 'au': 'au', 'perluasan': 'luas', 'alutisnya': 'alutisnya', 'melingkari': 'lingkar', 'nyatakan': 'nyata', 'tanam': 'tanam', 'cuplikan': 'cuplik', 'sepekan': 'pek', 'nnpresiden': 'nnpresiden', 'pekan': 'pekan', 'persis': 'persis', 'sd': 'sd', 'ttg': 'ttg', 'abis': 'abis', 'radarkorupsi': 'radarkorupsi', 'isu': 'isu', 'gulita': 'gulita', 'menunda': 'tunda', 'periodenndan': 'periodenndan', 'bplatform': 'bplatform', 'gambaran': 'gambar', 'nyata': 'nyata', 'argumenmu': 'argumen', 'cm': 'cm', 'ngandelin': 'ngandelin', 'issue': 'issue', 'maksa': 'maksa', 'kepastian': 'pasti', 'trs': 'trs', 'migrasi': 'migrasi', 'kapal': 'kapal', 'om': 'om', 'klu': 'klu', 'bdaripada': 'bdaripada', 'kesehatan': 'sehat', 'ekonominbukan': 'ekonominbukan', 'jopermadi': 'jopermadi', 'sampeyan': 'sampeyan', 'contoh': 'contoh', 'bandingin': 'bandingin', 'kalsel': 'kalsel', 'bahas': 'bahas', 'diluncurkan': 'luncur', 'niknsejahterakanindonesia': 'niknsejahterakanindonesia', 'gilaaa': 'gilaaa', 'kadesntapi': 'kadesntapi', 'nengok': 'nengok', 'fotofoto': 'fotofoto', 'nkalo': 'nkalo', 'hotel': 'hotel', 'yasonnab': 'yasonnab', 'barunindonesia': 'barunindonesia', 'barunnindonesia': 'barunnindonesia', 'membutuhkan': 'butuh', 'adil': 'adil', 'bsirqieee': 'bsirqieee', 'kelamin': 'kelamin', 'mrk': 'mrk', 'tahunya': 'tahu', 'msh': 'msh', 'iknnniknberdampakpositif': 'iknnniknberdampakpositif', 'bojk': 'bojk', 'keuangan': 'uang', 'berkantor': 'kantor', 'bsalah': 'bsalah', 'bsatriohendri': 'bsatriohendri', 'kecilan': 'kecil', 'ta': 'ta', 'kantong': 'kantong', 'kipp': 'kipp', 'bseperti': 'bseperti', 'pepatahnpengacara': 'pepatahnpengacara', 'argonya': 'argonya', 'pendek': 'pendek', 'pepatah': 'pepatah', 'ngkongroses': 'ngkongroses', 'olahraga': 'olahraga', 'bfull': 'bfull', 'tank': 'tank', 'hilang': 'hilang', 'panggung': 'panggung', 'habib': 'habib', 'ayuwulandariz': 'ayuwulandariz', 'bu': 'bu', 'bmodus': 'bmodus', 'dipakainnbiaya': 'dipakainnbiaya', 'triliunnnklik': 'triliunnnklik', 'baca': 'baca', 'plis': 'plis', 'my': 'my', 'bsinergi': 'bsinergi', 'sampah': 'sampah', 'bpietfitriady': 'bpietfitriady', 'ameliarfk': 'ameliarfk', 'kerakyatan': 'rakyat', 'nusantaranberdampak': 'nusantaranberdampak', 'timurnnniknberdampakpositif': 'timurnnniknberdampakpositif', 'dikembangkan': 'kembang', 'barundukung': 'barundukung', 'nusantarannniknberdampakpositif': 'nusantarannniknberdampakpositif', 'nusantaranuntuk': 'nusantaranuntuk', 'sentrisnujar': 'sentrisnujar', 'jokowinnniknberdampakpositif': 'jokowinnniknberdampakpositif', 'bsatiagustaman': 'bsatiagustaman', 'impor': 'impor', 'umbar': 'umbar', 'wkwkwk': 'wkwkwk', 'anthonybudiawan': 'anthonybudiawan', 'softbank': 'softbank', 'disahkan': 'sah', 'ahmaddshaddiq': 'ahmaddshaddiq', 'dukun': 'dukun', 'capitalism': 'capitalism', 'privilege': 'privilege', 'etalase': 'etalase', 'hegemoni': 'hegemoni', 'oligarkinnjokowi': 'oligarkinnjokowi', 'terjebak': 'jebak', 'budi': 'budi', 'danannkarena': 'danannkarena', 'diadili': 'adil', 'kaplingkan': 'kapling', 'apart': 'apart', 'salesmarketingnya': 'salesmarketingnya', 'dibantai': 'bantai', 'selesainnsesederhana': 'selesainnsesederhana', 'itunnmakanya': 'itunnmakanya', 'sirik': 'sirik', 'ngga': 'ngga', 'kebagian': 'bagi', 'wuuiiihhh': 'wuuiiihhh', 'mendoakan': 'doa', 'umurnmari': 'umurnmari', 'beliau': 'beliau', 'umur': 'umur', 'pinter': 'pinter', 'gibrantweet': 'gibrantweet', 'njokowi': 'njokowi', 'platform': 'platform', 'fitur': 'fitur', 'btawarkan': 'btawarkan', 'brayu': 'brayu', 'menurunkn': 'menurunkn', 'bala': 'bala', 'tentara': 'tentara', 'menjajah': 'jajah', 'menurunkan': 'turun', 'jutaan': 'juta', 'diazputransyah': 'diazputransyah', 'duniannnnnia': 'duniannnnnia', 'bisu': 'bisu', 'tercemar': 'cemar', 'secepatnya': 'cepat', 'steril': 'steril', 'mabuk': 'mabuk', 'radikalis': 'radikal', 'intoleran': 'intoleran', 'sdhlah': 'sdhlah', 'sebar': 'sebar', 'hoax': 'hoax', 'melulunindonesia': 'melulunindonesia', 'utuh': 'utuh', 'konstitusinya': 'konstitusi', 'dijunjung': 'junjung', 'bkementrian': 'bkementrian', 'modalnniknberdampakpositif': 'modalnniknberdampakpositif', 'orangorang': 'orangorang', 'kepentingan': 'penting', 'berpindahnya': 'pindah', 'kebanyakan': 'banyak', 'sok': 'sok', 'perduli': 'duli', 'marbunpm': 'marbunpm', 'tuduhan': 'tuduh', 'membabibuta': 'membabibuta', 'mshin': 'mshin', 'uunya': 'uunya', 'terangggg': 'terangggg', 'terusssss': 'terusssss', 'bravo': 'bravo', 'bpk': 'bpk', 'jangan': 'jangan', 'buzzerbab': 'buzzerbab', 'adlh': 'adlh', 'bmeninggalkan': 'bmeninggalkan', 'legacy': 'legacy', 'sepenting': 'penting', 'meninggalkan': 'tinggal', 'amalan': 'amal', 'jariyah': 'jariyah', 'jelajah': 'jelajah', 'nnjagatnusantara': 'nnjagatnusantara', 'hebatnya': 'hebat', 'urgen': 'urgen', 'bbakpiaduren': 'bbakpiaduren', 'idextratime': 'idextratime', 'kendor': 'kendor', 'bela': 'bela', 'sajatapi': 'sajatapi', 'harjonoabi': 'harjonoabi', 'projectmorg': 'projectmorg', 'iknid': 'iknid', 'didesain': 'desain', 'manusiamanusia': 'manusiamanusia', 'penghuninya': 'hun', 'mengakomodir': 'mengakomodir', 'ketar': 'ketar', 'ketir': 'tir', 'satupun': 'satu', 'kubu': 'kubu', 'berpikir': 'pikir', 'jokowin': 'jokowin', 'bmusniumar': 'bmusniumar', 'ahok': 'ahok', 'kau': 'kau', 'nikmati': 'nikmat', 'drunm': 'drunm', 'biarkan': 'biar', 'generasi': 'generasi', 'btxtdarihi': 'btxtdarihi', 'bayarnya': 'bayar', 'suntikan': 'sunti', 'iknkereta': 'iknkereta', 'membebani': 'beban', 'bsaat': 'bsaat', 'inkonstitusionalisasi': 'inkonstitusional', 'kehidupan': 'hidup', 'bernegara': 'negara', 'memupuk': 'pupuk', 'koalisi': 'koalisi', 'buzzerrp': 'buzzerrp', 'goblok': 'goblok', 'uyokback': 'uyokback', 'tewas': 'tewas', 'lubang': 'lubang', 'bekas': 'bekas', 'tambang': 'tambang', 'takdirnyan': 'takdirnyan', 'anakanak': 'anakanak', 'bprojectmorg': 'bprojectmorg', 'btanah': 'btanah', 'dikuasai': 'asai', 'kapitalis': 'kapitalis', 'tipikal': 'tipikal', 'indah': 'indah', 'kap': 'kap', 'kayaknya': 'kayak', 'mojadi': 'mojadi', 'free': 'free', 'for': 'for', 'bbisakah': 'bbisakah', 'berminatnini': 'berminatnini', 'tetangga': 'tetangga', 'bli': 'bli', 'tanahsana': 'tanahsana', 'mengatasi': 'atas', 'memangnya': 'memang', 'mambangun': 'mambangun', 'jkt': 'jkt', 'tempo': 'tempo', 'mengejar': 'kejar', 'track': 'track', 'record': 'record', 'nasdem': 'nasdem', 'membela': 'bela', 'sang': 'sang', 'penista': 'nista', 'bbm': 'bbm', 'omnibus': 'omnibus', 'law': 'law', 'oh': 'oh', 'bkn': 'bkn', 'jargon': 'jargon', 'politik': 'politik', 'deh': 'deh', 'pemeretaan': 'eta', 'bforum': 'bforum', 'bakohumas': 'bakohumas', 'diperlukan': 'perlu', 'informasi': 'informasi', 'sobatkom': 'sobatkom', 'diskominfokaltim': 'diskominfokaltim', 'bgarenghallu': 'bgarenghallu', 'gitu': 'gitu', 'mangkrak': 'mangkrak', 'loh': 'loh', 'ditundabukan': 'ditundabukan', 'jln': 'jln', 'widodoec': 'widodoec', 'paham': 'paham', 'sejarahnya': 'sejarah', 'bkangl': 'bkangl', 'haus': 'haus', 'hausteh': 'hausteh', 'tolteh': 'tolteh', 'tolyang': 'tolyang', 'lapar': 'lapar', 'roti': 'roti', 'iknnroti': 'iknnroti', 'nnkita': 'nnkita', 'anggap': 'anggap', 'urgent': 'urgent', 'memperluas': 'luas', 'siswa': 'siswa', 'kelulusan': 'kelulus', 'buang': 'buang', 'fungsinya': 'fungsi', 'kurang': 'kurang', 'menyuntikkan': 'suntik', 'keterpurukan': 'puruk', 'kesulitan': 'sulit', 'adrasilent': 'adrasilent', 'alas': 'alas', 'kaki': 'kaki', 'kedepak': 'depak', 'nhebat': 'nhebat', 'dijaman': 'jam', 'laseapoyhbb': 'laseapoyhbb', 'bmenpora': 'bmenpora', 'bjokowipres': 'bjokowipres', 'hrs': 'hrs', 'dibelintetap': 'dibelintetap', 'tirtoid': 'tirtoid', 'memperoleh': 'oleh', 'selesai': 'selesai', 'duluan': 'duluan', 'iknng': 'iknng', 'munafiklah': 'munafik', 'cnnindonesia': 'cnnindonesia', 'hatihati': 'hatihati', 'umurnya': 'umur', 'angkut': 'angkut', 'kekayaan': 'kaya', 'bumi': 'bumi', 'ka': 'ka', 'bnapsu': 'bnapsu', 'engga': 'engga', 'warasnikn': 'warasnikn', 'pintar': 'pintar', 'diperbodoh': 'bodoh', 'kemampuan': 'mampu', 'pikirannya': 'pikir', 'gankofpetojo': 'gankofpetojo', 'difoto': 'foto', 'mrt': 'mrt', 'blokgedung': 'blokgedung', 'kejaksaan': 'jaksa', 'agung': 'agung', 'berdiri': 'diri', 'tegak': 'tegak', 'lbh': 'lbh', 'terbakarnnrakyat': 'terbakarnnrakyat', 'boleh': 'boleh', 'mymine': 'mymine', 'ni': 'ni', 'kang': 'kang', 'edi': 'edi', 'mulyadi': 'mulyadi', 'kadung': 'kadung', 'gegara': 'gegara', 'protes': 'protes', 'gaterima': 'gaterima', 'jk': 'jk', 'tergusur': 'gusur', 'belanda': 'belanda', 'kuasai': 'kuasa', 'berperang': 'perang', 'ambisi': 'ambisi', 'berkoar': 'koar', 'kasta': 'kasta', 'bani': 'bani', 'bipang': 'bipang', 'penghuni': 'huni', 'kelak': 'kelak', 'perkawinan': 'kawin', 'babi': 'babi', 'keputusan': 'putus', 'memicu': 'picu', 'perbincangan': 'bincang', 'perihal': 'perihal', 'nama': 'nama', 'bkontenislamcom': 'bkontenislamcom', 'bcamarxoxo': 'bcamarxoxo', 'nusantaranjambinkotaduniauntuksemua': 'nusantaranjambinkotaduniauntuksemua', 'bdariatigunawan': 'bdariatigunawan', 'babangmeme': 'babangmeme', 'bgunakan': 'bgunakan', 'logika': 'logika', 'ganti': 'ganti', 'presidenbukan': 'presidenbukan', 'pdip': 'pdip', 'direzim': 'rezim', 'bpart': 'bpart', 'ngamuk': 'ngamuk', 'gara': 'gara', 'ditunda': 'tunda', 'kebal': 'kebal', 'nipu': 'nipu', 'negerikolam': 'negerikolam', 'gelombang': 'gelombang', 'iii': 'iii', 'pencaplokan': 'caplok', 'batas': 'batas', 'hak': 'hak', 'tumbuh': 'tumbuh', 'partai': 'partai', 'komunis': 'komunis', 'china': 'china', 'imigrasi': 'imigrasi', 'wna': 'wna', 'second': 'second', 'home': 'home', 'visa': 'visa', 'memancing': 'pancing', 'tiongkok': 'tiongkok', 'hubungannya': 'hubung', 'kesanaapa': 'kesanaapa', 'daerahnya': 'daerah', 'jga': 'jga', 'bersifat': 'sifat', 'bsentil': 'bsentil', 'lanyalla': 'lanyalla', 'ingatkan': 'ingat', 'prioritaskan': 'prioritas', 'lanyallaacademy': 'lanyallaacademy', 'mengumpulkan': 'kumpul', 'nmasih': 'nmasih', 'ingatkah': 'ingat', 'metverse': 'metverse', 'bernama': 'nama', 'awalpembiayaan': 'awalpembiayaan', 'sokong': 'sokong', 'bapln': 'bapln', 'premium': 'premium'}\n",
            "------------------------\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "final.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "P1E9P_UjXlPt",
        "outputId": "b4be4443-c4f8-4c79-d99c-7ac47cb8782f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  Sentimen                                       STOP REMOVAL  \\\n",
              "0  Positif  [brt, alshaibashihab, indonesia, ditangan, pre...   \n",
              "1  Negatif  [bprathumryan, pranjayabaguz, buset, miliar, u...   \n",
              "2  Negatif       [brt, bener, yah, sih, maksain, bangun, ikn]   \n",
              "3  Negatif  [brt, msaiddidu, pddk, yg, asn, yg, gajinya, s...   \n",
              "4  Negatif  [brt, hendryanalubis, pasti, mendukung, sapa, ...   \n",
              "\n",
              "                                            STEMMING  \n",
              "0  [brt, alshaibashihab, indonesia, tang, preside...  \n",
              "1  [bprathumryan, pranjayabaguz, buset, miliar, u...  \n",
              "2       [brt, bener, yah, sih, maksain, bangun, ikn]  \n",
              "3  [brt, msaiddidu, pddk, yg, asn, yg, gaji, sdh,...  \n",
              "4  [brt, hendryanalubis, pasti, dukung, sapa, yg,...  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-870a8eb3-ec51-441e-8980-5ffcfcca3d38\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Sentimen</th>\n",
              "      <th>STOP REMOVAL</th>\n",
              "      <th>STEMMING</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Positif</td>\n",
              "      <td>[brt, alshaibashihab, indonesia, ditangan, pre...</td>\n",
              "      <td>[brt, alshaibashihab, indonesia, tang, preside...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[bprathumryan, pranjayabaguz, buset, miliar, u...</td>\n",
              "      <td>[bprathumryan, pranjayabaguz, buset, miliar, u...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[brt, bener, yah, sih, maksain, bangun, ikn]</td>\n",
              "      <td>[brt, bener, yah, sih, maksain, bangun, ikn]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[brt, msaiddidu, pddk, yg, asn, yg, gajinya, s...</td>\n",
              "      <td>[brt, msaiddidu, pddk, yg, asn, yg, gaji, sdh,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[brt, hendryanalubis, pasti, mendukung, sapa, ...</td>\n",
              "      <td>[brt, hendryanalubis, pasti, dukung, sapa, yg,...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-870a8eb3-ec51-441e-8980-5ffcfcca3d38')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-870a8eb3-ec51-441e-8980-5ffcfcca3d38 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-870a8eb3-ec51-441e-8980-5ffcfcca3d38');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "kbba = pd.read_excel('/content/drive/MyDrive/Machine Learning 117/Analisis Sentimen IKN/Kamus/kamus_normalisasi.xlsx')"
      ],
      "metadata": {
        "id": "vsbWIFANXovI"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "kbba"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "LRwOgDzKXwe6",
        "outputId": "ef6437d2-059d-454a-9f3c-f5a30a27c4aa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Original Replacement\n",
              "0        abis       habis\n",
              "1          ad         ada\n",
              "2       adlah      adalah\n",
              "3        adlh      adalah\n",
              "4        adoh        aduh\n",
              "...       ...         ...\n",
              "1341    yowes    ya sudah\n",
              "1342      yuk         ayo\n",
              "1343      yup         iya\n",
              "1344     ywdh    ya sudah\n",
              "1345     zonk      kosong\n",
              "\n",
              "[1346 rows x 2 columns]"
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              "      <th>Replacement</th>\n",
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              "      <th>0</th>\n",
              "      <td>abis</td>\n",
              "      <td>habis</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ad</td>\n",
              "      <td>ada</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>adlah</td>\n",
              "      <td>adalah</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>adlh</td>\n",
              "      <td>adalah</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>adoh</td>\n",
              "      <td>aduh</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>1341</th>\n",
              "      <td>yowes</td>\n",
              "      <td>ya sudah</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1342</th>\n",
              "      <td>yuk</td>\n",
              "      <td>ayo</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1343</th>\n",
              "      <td>yup</td>\n",
              "      <td>iya</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1344</th>\n",
              "      <td>ywdh</td>\n",
              "      <td>ya sudah</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1345</th>\n",
              "      <td>zonk</td>\n",
              "      <td>kosong</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1346 rows × 2 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e9b488f7-27f8-4cc6-91ec-ed545c3e1b6f')\"\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-e9b488f7-27f8-4cc6-91ec-ed545c3e1b6f button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e9b488f7-27f8-4cc6-91ec-ed545c3e1b6f');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Normalisasi\n",
        "\n",
        "normalizad_word_dict = {}\n",
        "\n",
        "for index, row in kbba.iterrows():\n",
        "    if row[0] not in normalizad_word_dict:\n",
        "        normalizad_word_dict[row[0]] = row[1]\n",
        "\n",
        "def normalized_term(document):\n",
        "    return [normalizad_word_dict[term] if term in normalizad_word_dict else term for term in document]\n",
        "\n",
        "final['NORMALISASI'] = final['STEMMING'].apply(normalized_term)\n",
        "\n",
        "final['NORMALISASI'].head(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Y-WT3U6VXz4-",
        "outputId": "16f48e77-63b3-467c-a94c-8599a854117e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    [brt, alshaibashihab, indonesia, tang, preside...\n",
              "1    [bprathumryan, pranjayabaguz, buset, miliar, u...\n",
              "2         [brt, benar, yah, sih, memaksa, bangun, ikn]\n",
              "3    [brt, msaiddidu, pddk, yang, asn, yang, gaji, ...\n",
              "4    [brt, hendryanalubis, pasti, dukung, siapa, ya...\n",
              "5    [orang, berani, tidak, kalau, ikn, pindah, kal...\n",
              "6    [bpemerintah, susun, rencana, kembang, infrast...\n",
              "7    [brt, ikn, penting, entas, miskin, mas, joko, ...\n",
              "8    [bpemerintah, susun, rencana, kembang, infrast...\n",
              "9    [bzackyramadhani, alshaibashihab, bertanya, fu...\n",
              "Name: NORMALISASI, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def fit_normalisasi(text):\n",
        "    text = np.array(text)\n",
        "    text = ' '.join(text)\n",
        "\n",
        "    return text\n",
        "final['NORMALISASI'] = final['NORMALISASI'].apply(lambda x: fit_normalisasi(x))\n",
        "final.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 320
        },
        "id": "fafDcIdjX3Lb",
        "outputId": "608b13dd-c626-4cd3-882b-8e463401c391"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  Sentimen                                       STOP REMOVAL  \\\n",
              "0  Positif  [brt, alshaibashihab, indonesia, ditangan, pre...   \n",
              "1  Negatif  [bprathumryan, pranjayabaguz, buset, miliar, u...   \n",
              "2  Negatif       [brt, bener, yah, sih, maksain, bangun, ikn]   \n",
              "3  Negatif  [brt, msaiddidu, pddk, yg, asn, yg, gajinya, s...   \n",
              "4  Negatif  [brt, hendryanalubis, pasti, mendukung, sapa, ...   \n",
              "\n",
              "                                            STEMMING  \\\n",
              "0  [brt, alshaibashihab, indonesia, tang, preside...   \n",
              "1  [bprathumryan, pranjayabaguz, buset, miliar, u...   \n",
              "2       [brt, bener, yah, sih, maksain, bangun, ikn]   \n",
              "3  [brt, msaiddidu, pddk, yg, asn, yg, gaji, sdh,...   \n",
              "4  [brt, hendryanalubis, pasti, dukung, sapa, yg,...   \n",
              "\n",
              "                                         NORMALISASI  \n",
              "0  brt alshaibashihab indonesia tang presiden jok...  \n",
              "1  bprathumryan pranjayabaguz buset miliar usd ka...  \n",
              "2               brt benar yah sih memaksa bangun ikn  \n",
              "3  brt msaiddidu pddk yang asn yang gaji sudah ha...  \n",
              "4  brt hendryanalubis pasti dukung siapa yang bis...  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-af191495-bfbd-492f-b9e1-beab63b06e96\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
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              "\n",
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              "      <th>Sentimen</th>\n",
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              "      <th>0</th>\n",
              "      <td>Positif</td>\n",
              "      <td>[brt, alshaibashihab, indonesia, ditangan, pre...</td>\n",
              "      <td>[brt, alshaibashihab, indonesia, tang, preside...</td>\n",
              "      <td>brt alshaibashihab indonesia tang presiden jok...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[bprathumryan, pranjayabaguz, buset, miliar, u...</td>\n",
              "      <td>[bprathumryan, pranjayabaguz, buset, miliar, u...</td>\n",
              "      <td>bprathumryan pranjayabaguz buset miliar usd ka...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[brt, bener, yah, sih, maksain, bangun, ikn]</td>\n",
              "      <td>[brt, bener, yah, sih, maksain, bangun, ikn]</td>\n",
              "      <td>brt benar yah sih memaksa bangun ikn</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[brt, msaiddidu, pddk, yg, asn, yg, gajinya, s...</td>\n",
              "      <td>[brt, msaiddidu, pddk, yg, asn, yg, gaji, sdh,...</td>\n",
              "      <td>brt msaiddidu pddk yang asn yang gaji sudah ha...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[brt, hendryanalubis, pasti, mendukung, sapa, ...</td>\n",
              "      <td>[brt, hendryanalubis, pasti, dukung, sapa, yg,...</td>\n",
              "      <td>brt hendryanalubis pasti dukung siapa yang bis...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-af191495-bfbd-492f-b9e1-beab63b06e96')\"\n",
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              "              style=\"display:none;\">\n",
              "        \n",
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              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-af191495-bfbd-492f-b9e1-beab63b06e96 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-af191495-bfbd-492f-b9e1-beab63b06e96');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "final.to_excel(\"/content/drive/MyDrive/Machine Learning 117/Analisis Sentimen IKN/Hasil QE/Normalisasi.xlsx\")"
      ],
      "metadata": {
        "id": "Z39YoueRX7Gf"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#NORMALISASI NEGASI\n",
        "def convert_negasi(text):\n",
        "    text = re.sub(\"tidak \", 'tidak', text, flags=re.MULTILINE)\n",
        "    text = re.sub(\"jangan \", 'jangan', text, flags=re.MULTILINE)\n",
        "    text = re.sub(\"belum \", 'belum', text, flags=re.MULTILINE)\n",
        "    text = re.sub(\"bukan \", 'bukan', text, flags=re.MULTILINE)\n",
        "    text = re.sub(\"tanpa \", 'tanpa', text, flags=re.MULTILINE)\n",
        "    text = re.sub(\"bukanlah \", 'bukanlah', text, flags=re.MULTILINE)\n",
        "    text = re.sub(\"tak \", 'tak', text, flags=re.MULTILINE)\n",
        "    text = re.sub(\"anti \", 'anti', text, flags=re.MULTILINE)\n",
        "    return text\n",
        "final['NORMALISASI']= final['NORMALISASI'].apply(lambda x: convert_negasi(x))\n",
        "final"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 641
        },
        "id": "Nq7R4CbmYBY4",
        "outputId": "b5b8e38c-2ae0-4fb2-f660-c2de1a3187f9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Sentimen                                       STOP REMOVAL  \\\n",
              "0     Positif  [brt, alshaibashihab, indonesia, ditangan, pre...   \n",
              "1     Negatif  [bprathumryan, pranjayabaguz, buset, miliar, u...   \n",
              "2     Negatif       [brt, bener, yah, sih, maksain, bangun, ikn]   \n",
              "3     Negatif  [brt, msaiddidu, pddk, yg, asn, yg, gajinya, s...   \n",
              "4     Negatif  [brt, hendryanalubis, pasti, mendukung, sapa, ...   \n",
              "...       ...                                                ...   \n",
              "2172  Positif  [bprogres, ikn, tahap, awalpembiayaan, masih, ...   \n",
              "2173  Positif  [bapln, garap, kawasan, hunian, super, premium...   \n",
              "2174  Negatif  [brt, hukumdan, wuiih, serius, kek, nya, pinda...   \n",
              "2175  Negatif  [brt, lanyallaacademy, urgensinya, harus, meng...   \n",
              "2176  Positif  [bmasyarakat, kalimantan, timur, dukung, pemba...   \n",
              "\n",
              "                                               STEMMING  \\\n",
              "0     [brt, alshaibashihab, indonesia, tang, preside...   \n",
              "1     [bprathumryan, pranjayabaguz, buset, miliar, u...   \n",
              "2          [brt, bener, yah, sih, maksain, bangun, ikn]   \n",
              "3     [brt, msaiddidu, pddk, yg, asn, yg, gaji, sdh,...   \n",
              "4     [brt, hendryanalubis, pasti, dukung, sapa, yg,...   \n",
              "...                                                 ...   \n",
              "2172  [bprogres, ikn, tahap, awalpembiayaan, masih, ...   \n",
              "2173  [bapln, garap, kawasan, huni, super, premium, ...   \n",
              "2174  [brt, hukumdan, wuiih, serius, kek, nya, pinda...   \n",
              "2175  [brt, lanyallaacademy, urgensi, harus, kumpul,...   \n",
              "2176  [bmasyarakat, kalimantan, timur, dukung, bangu...   \n",
              "\n",
              "                                            NORMALISASI  \n",
              "0     brt alshaibashihab indonesia tang presiden jok...  \n",
              "1     bprathumryan pranjayabaguz buset miliar usd ka...  \n",
              "2                  brt benar yah sih memaksa bangun ikn  \n",
              "3     brt msaiddidu pddk yang asn yang gaji sudah ha...  \n",
              "4     brt hendryanalubis pasti dukung siapa yang bis...  \n",
              "...                                                 ...  \n",
              "2172  bprogres ikn tahap awalpembiayaan masih sokong...  \n",
              "2173   bapln garap kawasan huni super premium ikn minat  \n",
              "2174  brt hukumdan wuiih serius seperti nya pindah a...  \n",
              "2175  brt lanyallaacademy urgensi harus kumpul kepal...  \n",
              "2176     bmasyarakat kalimantan timur dukung bangun ikn  \n",
              "\n",
              "[2177 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-9482670e-59f0-45a1-9354-d322338cda67\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    .dataframe thead th {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Sentimen</th>\n",
              "      <th>STOP REMOVAL</th>\n",
              "      <th>STEMMING</th>\n",
              "      <th>NORMALISASI</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Positif</td>\n",
              "      <td>[brt, alshaibashihab, indonesia, ditangan, pre...</td>\n",
              "      <td>[brt, alshaibashihab, indonesia, tang, preside...</td>\n",
              "      <td>brt alshaibashihab indonesia tang presiden jok...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[bprathumryan, pranjayabaguz, buset, miliar, u...</td>\n",
              "      <td>[bprathumryan, pranjayabaguz, buset, miliar, u...</td>\n",
              "      <td>bprathumryan pranjayabaguz buset miliar usd ka...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[brt, bener, yah, sih, maksain, bangun, ikn]</td>\n",
              "      <td>[brt, bener, yah, sih, maksain, bangun, ikn]</td>\n",
              "      <td>brt benar yah sih memaksa bangun ikn</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[brt, msaiddidu, pddk, yg, asn, yg, gajinya, s...</td>\n",
              "      <td>[brt, msaiddidu, pddk, yg, asn, yg, gaji, sdh,...</td>\n",
              "      <td>brt msaiddidu pddk yang asn yang gaji sudah ha...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[brt, hendryanalubis, pasti, mendukung, sapa, ...</td>\n",
              "      <td>[brt, hendryanalubis, pasti, dukung, sapa, yg,...</td>\n",
              "      <td>brt hendryanalubis pasti dukung siapa yang bis...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2172</th>\n",
              "      <td>Positif</td>\n",
              "      <td>[bprogres, ikn, tahap, awalpembiayaan, masih, ...</td>\n",
              "      <td>[bprogres, ikn, tahap, awalpembiayaan, masih, ...</td>\n",
              "      <td>bprogres ikn tahap awalpembiayaan masih sokong...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2173</th>\n",
              "      <td>Positif</td>\n",
              "      <td>[bapln, garap, kawasan, hunian, super, premium...</td>\n",
              "      <td>[bapln, garap, kawasan, huni, super, premium, ...</td>\n",
              "      <td>bapln garap kawasan huni super premium ikn minat</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2174</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[brt, hukumdan, wuiih, serius, kek, nya, pinda...</td>\n",
              "      <td>[brt, hukumdan, wuiih, serius, kek, nya, pinda...</td>\n",
              "      <td>brt hukumdan wuiih serius seperti nya pindah a...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2175</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[brt, lanyallaacademy, urgensinya, harus, meng...</td>\n",
              "      <td>[brt, lanyallaacademy, urgensi, harus, kumpul,...</td>\n",
              "      <td>brt lanyallaacademy urgensi harus kumpul kepal...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2176</th>\n",
              "      <td>Positif</td>\n",
              "      <td>[bmasyarakat, kalimantan, timur, dukung, pemba...</td>\n",
              "      <td>[bmasyarakat, kalimantan, timur, dukung, bangu...</td>\n",
              "      <td>bmasyarakat kalimantan timur dukung bangun ikn</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2177 rows × 4 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-9482670e-59f0-45a1-9354-d322338cda67')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-9482670e-59f0-45a1-9354-d322338cda67 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-9482670e-59f0-45a1-9354-d322338cda67');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from wordcloud import WordCloud\n",
        "\n",
        "\n",
        "negative_words =' '.join([text for text in final['NORMALISASI'][final['Sentimen'] == 'Negatif']])\n",
        "\n",
        "wordcloud = WordCloud(width=800, height=500, random_state = 0, max_font_size = 110).generate(negative_words)\n",
        "plt.figure(figsize=(10, 7))\n",
        "plt.imshow(wordcloud, interpolation=\"bilinear\")\n",
        "plt.axis('off')\n",
        "plt.title('The Negative Words')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 396
        },
        "id": "1_4N2B5aYEzy",
        "outputId": "363d97f1-f2ea-49b7-ce53-4b75088c50d7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from wordcloud import WordCloud\n",
        "\n",
        "positif_words =' '.join([text for text in final['NORMALISASI'][final['Sentimen'] == 'Positif']])\n",
        "\n",
        "wordcloud = WordCloud(width=800, height=500, random_state = 0, max_font_size = 110).generate(positif_words)\n",
        "plt.figure(figsize=(10, 7))\n",
        "plt.imshow(wordcloud, interpolation=\"bilinear\")\n",
        "plt.axis('off')\n",
        "plt.title('The Positif Words')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 396
        },
        "id": "5FQnsYJeYMjn",
        "outputId": "1c5b91b5-99a6-4029-e985-8e31788fa78f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Merubah Sentimen ke Polarity\n",
        "#Konversi Sentimen Ke Polaritas\n",
        "def convert(polarity):\n",
        "    if polarity == 'Positif':\n",
        "        return 1\n",
        "    else:\n",
        "        return -1"
      ],
      "metadata": {
        "id": "a2yU-y40YQzg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "final['Polarity'] = final['Sentimen'].apply(convert)\n",
        "final\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 641
        },
        "id": "focysIjGYU26",
        "outputId": "eaf083ee-e462-4ffb-8b43-8e07cde82624"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Sentimen                                       STOP REMOVAL  \\\n",
              "0     Positif  [brt, alshaibashihab, indonesia, ditangan, pre...   \n",
              "1     Negatif  [bprathumryan, pranjayabaguz, buset, miliar, u...   \n",
              "2     Negatif       [brt, bener, yah, sih, maksain, bangun, ikn]   \n",
              "3     Negatif  [brt, msaiddidu, pddk, yg, asn, yg, gajinya, s...   \n",
              "4     Negatif  [brt, hendryanalubis, pasti, mendukung, sapa, ...   \n",
              "...       ...                                                ...   \n",
              "2172  Positif  [bprogres, ikn, tahap, awalpembiayaan, masih, ...   \n",
              "2173  Positif  [bapln, garap, kawasan, hunian, super, premium...   \n",
              "2174  Negatif  [brt, hukumdan, wuiih, serius, kek, nya, pinda...   \n",
              "2175  Negatif  [brt, lanyallaacademy, urgensinya, harus, meng...   \n",
              "2176  Positif  [bmasyarakat, kalimantan, timur, dukung, pemba...   \n",
              "\n",
              "                                               STEMMING  \\\n",
              "0     [brt, alshaibashihab, indonesia, tang, preside...   \n",
              "1     [bprathumryan, pranjayabaguz, buset, miliar, u...   \n",
              "2          [brt, bener, yah, sih, maksain, bangun, ikn]   \n",
              "3     [brt, msaiddidu, pddk, yg, asn, yg, gaji, sdh,...   \n",
              "4     [brt, hendryanalubis, pasti, dukung, sapa, yg,...   \n",
              "...                                                 ...   \n",
              "2172  [bprogres, ikn, tahap, awalpembiayaan, masih, ...   \n",
              "2173  [bapln, garap, kawasan, huni, super, premium, ...   \n",
              "2174  [brt, hukumdan, wuiih, serius, kek, nya, pinda...   \n",
              "2175  [brt, lanyallaacademy, urgensi, harus, kumpul,...   \n",
              "2176  [bmasyarakat, kalimantan, timur, dukung, bangu...   \n",
              "\n",
              "                                            NORMALISASI  Polarity  \n",
              "0     brt alshaibashihab indonesia tang presiden jok...         1  \n",
              "1     bprathumryan pranjayabaguz buset miliar usd ka...        -1  \n",
              "2                  brt benar yah sih memaksa bangun ikn        -1  \n",
              "3     brt msaiddidu pddk yang asn yang gaji sudah ha...        -1  \n",
              "4     brt hendryanalubis pasti dukung siapa yang bis...        -1  \n",
              "...                                                 ...       ...  \n",
              "2172  bprogres ikn tahap awalpembiayaan masih sokong...         1  \n",
              "2173   bapln garap kawasan huni super premium ikn minat         1  \n",
              "2174  brt hukumdan wuiih serius seperti nya pindah a...        -1  \n",
              "2175  brt lanyallaacademy urgensi harus kumpul kepal...        -1  \n",
              "2176     bmasyarakat kalimantan timur dukung bangun ikn         1  \n",
              "\n",
              "[2177 rows x 5 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-74f9ed2a-6720-466f-90b3-218aaac41e78\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
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              "      <th></th>\n",
              "      <th>Sentimen</th>\n",
              "      <th>STOP REMOVAL</th>\n",
              "      <th>STEMMING</th>\n",
              "      <th>NORMALISASI</th>\n",
              "      <th>Polarity</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Positif</td>\n",
              "      <td>[brt, alshaibashihab, indonesia, ditangan, pre...</td>\n",
              "      <td>[brt, alshaibashihab, indonesia, tang, preside...</td>\n",
              "      <td>brt alshaibashihab indonesia tang presiden jok...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[bprathumryan, pranjayabaguz, buset, miliar, u...</td>\n",
              "      <td>[bprathumryan, pranjayabaguz, buset, miliar, u...</td>\n",
              "      <td>bprathumryan pranjayabaguz buset miliar usd ka...</td>\n",
              "      <td>-1</td>\n",
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              "      <th>2</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[brt, bener, yah, sih, maksain, bangun, ikn]</td>\n",
              "      <td>[brt, bener, yah, sih, maksain, bangun, ikn]</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[brt, msaiddidu, pddk, yg, asn, yg, gajinya, s...</td>\n",
              "      <td>[brt, msaiddidu, pddk, yg, asn, yg, gaji, sdh,...</td>\n",
              "      <td>brt msaiddidu pddk yang asn yang gaji sudah ha...</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[brt, hendryanalubis, pasti, mendukung, sapa, ...</td>\n",
              "      <td>[brt, hendryanalubis, pasti, dukung, sapa, yg,...</td>\n",
              "      <td>brt hendryanalubis pasti dukung siapa yang bis...</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2172</th>\n",
              "      <td>Positif</td>\n",
              "      <td>[bprogres, ikn, tahap, awalpembiayaan, masih, ...</td>\n",
              "      <td>[bprogres, ikn, tahap, awalpembiayaan, masih, ...</td>\n",
              "      <td>bprogres ikn tahap awalpembiayaan masih sokong...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2173</th>\n",
              "      <td>Positif</td>\n",
              "      <td>[bapln, garap, kawasan, hunian, super, premium...</td>\n",
              "      <td>[bapln, garap, kawasan, huni, super, premium, ...</td>\n",
              "      <td>bapln garap kawasan huni super premium ikn minat</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2174</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[brt, hukumdan, wuiih, serius, kek, nya, pinda...</td>\n",
              "      <td>[brt, hukumdan, wuiih, serius, kek, nya, pinda...</td>\n",
              "      <td>brt hukumdan wuiih serius seperti nya pindah a...</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2175</th>\n",
              "      <td>Negatif</td>\n",
              "      <td>[brt, lanyallaacademy, urgensinya, harus, meng...</td>\n",
              "      <td>[brt, lanyallaacademy, urgensi, harus, kumpul,...</td>\n",
              "      <td>brt lanyallaacademy urgensi harus kumpul kepal...</td>\n",
              "      <td>-1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2176</th>\n",
              "      <td>Positif</td>\n",
              "      <td>[bmasyarakat, kalimantan, timur, dukung, pemba...</td>\n",
              "      <td>[bmasyarakat, kalimantan, timur, dukung, bangu...</td>\n",
              "      <td>bmasyarakat kalimantan timur dukung bangun ikn</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2177 rows × 5 columns</p>\n",
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              "          const element = document.querySelector('#df-74f9ed2a-6720-466f-90b3-218aaac41e78');\n",
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            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "final.to_excel(\"/content/drive/MyDrive/Machine Learning 117/Analisis Sentimen IKN/Hasil QE/Setelah Pre-Processing.xlsx\")"
      ],
      "metadata": {
        "id": "LcMA8JABYYR-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Split Data\n",
        "Train_X, Test_X, Train_Y, Test_Y = model_selection.train_test_split(final['NORMALISASI'],final['Polarity'], test_size=0.1, random_state=30)\n",
        "#print(X_Test)"
      ],
      "metadata": {
        "id": "J3Bu3id1YelQ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "Encoder = LabelEncoder()\n",
        "Train_Y = Encoder.fit_transform(Train_Y)\n",
        "Test_Y = Encoder.fit_transform(Test_Y)"
      ],
      "metadata": {
        "id": "6YLhrd1PYjjl"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# PEMBOBOTAN TF-IDF"
      ],
      "metadata": {
        "id": "BVN7c_ahYsob"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "Tfidf_vect = TfidfVectorizer()\n",
        "Tfidf_vect.fit(final['NORMALISASI'])\n",
        "\n",
        "Train_X_Tfidf = Tfidf_vect.transform(Train_X)\n",
        "Test_X_Tfidf = Tfidf_vect.transform(Test_X)"
      ],
      "metadata": {
        "id": "9-vlhdbSYw9S"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "Train_X_Tfidf.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gbmIlHEIY1f9",
        "outputId": "a2e7ec1d-9998-473e-fbab-660f29ff0849"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1959, 2136)"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Train_Y.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "imhplMBxY5rM",
        "outputId": "1e100f23-9f1e-4f0b-97db-837d04383ce4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1959,)"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(Train_X_Tfidf)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eAMGeugJY7-l",
        "outputId": "c1ea41bb-828e-4d68-bc97-f97c7b0cf161"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "  (0, 1890)\t0.3192559249260791\n",
            "  (0, 1715)\t0.3192559249260791\n",
            "  (0, 1624)\t0.22853996841885849\n",
            "  (0, 1232)\t0.3192559249260791\n",
            "  (0, 984)\t0.20910271111265352\n",
            "  (0, 950)\t0.24796134345336104\n",
            "  (0, 888)\t0.18282757795129892\n",
            "  (0, 427)\t0.09627162483455953\n",
            "  (0, 219)\t0.30128691509913164\n",
            "  (0, 156)\t0.3192559249260791\n",
            "  (0, 126)\t0.3192559249260791\n",
            "  (0, 71)\t0.3158093008236477\n",
            "  (0, 35)\t0.3158093008236477\n",
            "  (1, 2100)\t0.2595761337654515\n",
            "  (1, 1886)\t0.5094999434532351\n",
            "  (1, 1881)\t0.2602058559258072\n",
            "  (1, 1389)\t0.519152267530903\n",
            "  (1, 845)\t0.08565753948388173\n",
            "  (1, 808)\t0.24506346566152237\n",
            "  (1, 427)\t0.11522186394597704\n",
            "  (1, 291)\t0.2280640644250436\n",
            "  (1, 162)\t0.2602058559258072\n",
            "  (1, 152)\t0.2602058559258072\n",
            "  (1, 1)\t0.2602058559258072\n",
            "  (2, 1673)\t0.40728722483186147\n",
            "  :\t:\n",
            "  (1956, 135)\t0.27186471769937676\n",
            "  (1957, 1998)\t0.17564708574960286\n",
            "  (1957, 1899)\t0.37409711182229516\n",
            "  (1957, 1823)\t0.24873028888658796\n",
            "  (1957, 1245)\t0.179317973503729\n",
            "  (1957, 1114)\t0.21501331529577783\n",
            "  (1957, 978)\t0.4051568771248394\n",
            "  (1957, 970)\t0.17861093278157608\n",
            "  (1957, 879)\t0.392771975765703\n",
            "  (1957, 710)\t0.24709776101507464\n",
            "  (1957, 662)\t0.15587313745322806\n",
            "  (1957, 559)\t0.2567364229026147\n",
            "  (1957, 427)\t0.10005334254422972\n",
            "  (1957, 22)\t0.42112379200597017\n",
            "  (1958, 2100)\t0.2595761337654515\n",
            "  (1958, 1886)\t0.5094999434532351\n",
            "  (1958, 1881)\t0.2602058559258072\n",
            "  (1958, 1389)\t0.519152267530903\n",
            "  (1958, 845)\t0.08565753948388173\n",
            "  (1958, 808)\t0.24506346566152237\n",
            "  (1958, 427)\t0.11522186394597704\n",
            "  (1958, 291)\t0.2280640644250436\n",
            "  (1958, 162)\t0.2602058559258072\n",
            "  (1958, 152)\t0.2602058559258072\n",
            "  (1958, 1)\t0.2602058559258072\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(Test_X_Tfidf)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "w30Yipv7Y-M0",
        "outputId": "4407be13-3a9f-4313-e997-7bee3aa38e63"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "  (0, 1895)\t0.6860235411743747\n",
            "  (0, 1436)\t0.21333833800765922\n",
            "  (0, 845)\t0.11502241279538358\n",
            "  (0, 202)\t0.6860235411743747\n",
            "  (1, 1647)\t0.45987397123078894\n",
            "  (1, 845)\t0.11661403139724562\n",
            "  (1, 330)\t0.6955163678584297\n",
            "  (1, 160)\t0.5396054858011762\n",
            "  (2, 2100)\t0.2595761337654515\n",
            "  (2, 1886)\t0.5094999434532351\n",
            "  (2, 1881)\t0.2602058559258072\n",
            "  (2, 1389)\t0.519152267530903\n",
            "  (2, 845)\t0.08565753948388173\n",
            "  (2, 808)\t0.24506346566152237\n",
            "  (2, 427)\t0.11522186394597704\n",
            "  (2, 291)\t0.2280640644250436\n",
            "  (2, 162)\t0.2602058559258072\n",
            "  (2, 152)\t0.2602058559258072\n",
            "  (2, 1)\t0.2602058559258072\n",
            "  (3, 1998)\t0.26472569150503106\n",
            "  (3, 1251)\t0.3422136595127438\n",
            "  (3, 1245)\t0.27025825297624007\n",
            "  (3, 970)\t0.26919263982760533\n",
            "  (3, 845)\t0.11210305380015483\n",
            "  (3, 662)\t0.23492347694392562\n",
            "  :\t:\n",
            "  (216, 1739)\t0.32814676141552196\n",
            "  (216, 1491)\t0.3439638235071796\n",
            "  (216, 1436)\t0.14457835732841395\n",
            "  (216, 1105)\t0.39204769680934193\n",
            "  (216, 1022)\t0.32037988953436813\n",
            "  (216, 1015)\t0.3774299584035735\n",
            "  (216, 845)\t0.07795013148227611\n",
            "  (216, 772)\t0.27653664861838434\n",
            "  (216, 628)\t0.3774299584035735\n",
            "  (216, 427)\t0.10485427784102892\n",
            "  (216, 65)\t0.3439638235071796\n",
            "  (217, 2124)\t0.4132329623405887\n",
            "  (217, 1889)\t0.28426222330626777\n",
            "  (217, 1853)\t0.28426222330626777\n",
            "  (217, 1668)\t0.285796827892614\n",
            "  (217, 1413)\t0.28737466641670156\n",
            "  (217, 1386)\t0.28737466641670156\n",
            "  (217, 932)\t0.2745573498199242\n",
            "  (217, 845)\t0.07506133386924196\n",
            "  (217, 650)\t0.26005862268110497\n",
            "  (217, 427)\t0.1009684243885244\n",
            "  (217, 268)\t0.285796827892614\n",
            "  (217, 136)\t0.126472788795612\n",
            "  (217, 125)\t0.285796827892614\n",
            "  (217, 10)\t0.28737466641670156\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# QUERY EXPANSION\n"
      ],
      "metadata": {
        "id": "h5J2Wotj9ULs"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import expansion\n",
        "import xlrd\n",
        "\n",
        "\n",
        "queryList = []\n",
        "# we want to keep the list of unique queries\n",
        "uniqueQuery = []\n",
        "\n",
        "workbook = xlrd.open_workbook('data/m.xls')\n",
        "sheet_names = workbook.sheet_names()\n",
        "xl_sheet = workbook.sheet_by_name(sheet_names[0])\n",
        "\n",
        "for row_idx in range(0, xl_sheet.nrows):    # Iterate through rows\n",
        "        cell_id = xl_sheet.cell(row_idx, 0).value  # Get id cell\n",
        "        cell_topic = xl_sheet.cell(row_idx, 2).value  # Get topic cell\n",
        "        if str(cell_topic) not in uniqueQuery:\n",
        "            queryList.append(str(cell_id) + \",\" + str(cell_topic))\n",
        "            uniqueQuery.append(str(cell_topic))\n",
        "\n",
        "# the list of queries that we want to expand\n",
        "expansion.run(queryList)"
      ],
      "metadata": {
        "id": "z5AjVAIn9ZMm"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# METODE KLASIFIKASI SVM"
      ],
      "metadata": {
        "id": "KV4vRWIYZDG7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "hyperparameters = {'kernel':('linear', 'rbf'), 'C':[1, 10]}\n",
        "svm = SVC()\n",
        "svm_tuned = GridSearchCV(svm, hyperparameters)"
      ],
      "metadata": {
        "id": "OodbSZhqZFLi"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "svm_tuned.fit(Train_X_Tfidf, Train_Y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "__ptdbCzZGpq",
        "outputId": "2363dd1a-3943-4473-e4f8-0ba2aa025e0f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "GridSearchCV(estimator=SVC(),\n",
              "             param_grid={'C': [1, 10], 'kernel': ('linear', 'rbf')})"
            ]
          },
          "metadata": {},
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "svm = SVC(C=1, kernel='linear', degree=3, gamma='scale')\n",
        "svm.fit(Train_X_Tfidf,Train_Y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Yr0leWMoZNT8",
        "outputId": "f9e0d750-8a99-4c65-d9f4-8d8a1f51b1b6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "SVC(C=1, kernel='linear')"
            ]
          },
          "metadata": {},
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "filename = 'model_svm_IKN.pkl'\n",
        "pickle.dump(svm, open(filename, 'wb'))"
      ],
      "metadata": {
        "id": "SryhB4SaZQL4"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "loaded_model = pickle.load(open(filename, 'rb'))\n",
        "result = loaded_model.score(Test_X_Tfidf, Test_Y)\n",
        "print(result)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8kRj0jUSZSIc",
        "outputId": "8a549304-3b7d-4053-96d6-641d3a9acb2d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.926605504587156\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# EVALUASI KERJA"
      ],
      "metadata": {
        "id": "G69T7gBiZcN8"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# HASIL AKURASI, RECALL, PRECISSION, F1 SCORE\n",
        "\n",
        "predict_test = svm.predict(Test_X_Tfidf)\n",
        "\n",
        "print(\"SVM Accuracy Score = \", accuracy_score(predict_test, Test_Y)*100)\n",
        "print(\"SVM Precision Score = \", recall_score(predict_test, Test_Y)*100)\n",
        "print(\"SVM Recall Score = \", precision_score(predict_test, Test_Y)*100)\n",
        "print(\"SVM f1 Score = \", f1_score(predict_test, Test_Y)*100)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OWaJNffGZirN",
        "outputId": "f61e58fa-7ed2-46a3-c435-cf9e4ab82b25"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "SVM Accuracy Score =  92.66055045871559\n",
            "SVM Precision Score =  93.79310344827586\n",
            "SVM Recall Score =  95.1048951048951\n",
            "SVM f1 Score =  94.44444444444446\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "report = classification_report(Test_Y, predict_test)\n",
        "print(report) # print classification_report"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "y10_oNIXZmdq",
        "outputId": "f8c55041-bbce-49cf-b411-8aba5415f9e6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.90      0.88      0.89        75\n",
            "           1       0.94      0.95      0.94       143\n",
            "\n",
            "    accuracy                           0.93       218\n",
            "   macro avg       0.92      0.92      0.92       218\n",
            "weighted avg       0.93      0.93      0.93       218\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Confusion Matrix\n",
        "from sklearn.metrics import confusion_matrix\n",
        "from sklearn.utils.multiclass import unique_labels\n",
        "\n",
        "def plot_confusion_matrix(y_true, y_pred, classes,\n",
        "                         normalize=False,\n",
        "                         title=None,\n",
        "                         cmap=plt.cm.Blues):\n",
        "\n",
        "    \"\"\"\n",
        "    This functions\n",
        "    normalize=True\n",
        "    \"\"\"\n",
        "\n",
        "    if not title:\n",
        "        if normalize:\n",
        "            title = 'Normalized confusion matrix'\n",
        "        else:\n",
        "            title = 'Confusion matrix, without normalization'\n",
        "\n",
        "    cm = confusion_matrix(y_true, y_pred)\n",
        "\n",
        "    classes = classes[unique_labels(y_true, y_pred)]\n",
        "    if normalize:\n",
        "        cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n",
        "        print(\"Normalized confusion matrix\")\n",
        "    else:\n",
        "        title = 'Confusion matrix, without normalization'\n",
        "\n",
        "    print(cm)\n",
        "\n",
        "    fig, ax = plt.subplots()\n",
        "    im = ax.imshow(cm, interpolation='nearest', cmap=cmap)\n",
        "    ax.figure.colorbar(im, ax=ax)\n",
        "\n",
        "    ax.set(xticks=np.arange(cm.shape[1]),\n",
        "          yticks=np.arange(cm.shape[0]),\n",
        "          xticklabels=classes, yticklabels=classes,\n",
        "          title=title,\n",
        "          ylabel='True label',\n",
        "          xlabel='Predicted label')\n",
        "\n",
        "    plt.setp(ax.get_xticklabels(), rotation=45, ha=\"right\",\n",
        "            rotation_mode=\"anchor\")\n",
        "\n",
        "    fmt= '.2f' if normalize else 'd'\n",
        "    thresh = cm.max() / 2.\n",
        "    for i in range(cm.shape[0]):\n",
        "        for j in range(cm.shape[1]):\n",
        "            ax.text(j, i, format(cm[i, j], fmt),\n",
        "                   ha=\"center\", va=\"center\",\n",
        "                   color=\"white\" if cm[i, j] > thresh else \"black\")\n",
        "            fig.tight_layout()\n",
        "            return ax\n",
        "\n",
        "    np.set_printoptions(precision=2)\n",
        "\n",
        ""
      ],
      "metadata": {
        "id": "M87jycEqZo8A"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "class_names = Test_Y\n",
        "plot_confusion_matrix(Test_Y, predict_test, classes=class_names,\n",
        "                     title='Confusion matrix, without normalization')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 332
        },
        "id": "EVCD668UZr3d",
        "outputId": "42f87326-1465-48c3-a54e-0c862a588f45"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[ 66   9]\n",
            " [  7 136]]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print('CONFUSION MATRIX')\n",
        "print('[TP  FN]')\n",
        "print('[FP  TN]')\n",
        "confusion_matrix(Test_Y, predict_test, labels=[1, 0])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VbnF8sO-ZvCC",
        "outputId": "15f73fd6-b3cb-4c1d-b2b6-e8418d96e112"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "CONFUSION MATRIX\n",
            "[TP  FN]\n",
            "[FP  TN]\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[136,   7],\n",
              "       [  9,  66]])"
            ]
          },
          "metadata": {},
          "execution_count": 68
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# HASIL AKURASI, RECALL, PRECISSION, F1 SCORE DENGAN CONFUSION MATRIX\n",
        "\n",
        "TP = 87\n",
        "FN = 6\n",
        "FP = 0\n",
        "TN = 107\n",
        "\n",
        "accuracy = (TP+TN)/(TP+FN+FP+TN)\n",
        "precision = TP/(TP+FP)\n",
        "recall = TP/(TP+FN)\n",
        "f1 = 2 *precision*recall/(precision+recall)\n",
        "\n",
        "\n",
        "print(\"HASIL AKURASI, RECALL, PRECISION, F1 SCORE DENGAN CONFUSION MATRIX \\n\")\n",
        "\n",
        "print(\"SVM Accuracy Score = \", accuracy*100 ,\"%\")\n",
        "print(\"SVM Precision Score = \", precision*100,\"%\")\n",
        "print(\"SVM Recall Score = \", recall*100,\"%\")\n",
        "print(\"SVM f1 Score = \", f1*100,\"%\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XtlmDt-5Zy8z",
        "outputId": "ae682bbe-a4d5-4d7d-a67d-67ca8973cea8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "HASIL AKURASI, RECALL, PRECISION, F1 SCORE DENGAN CONFUSION MATRIX \n",
            "\n",
            "SVM Accuracy Score =  97.0 %\n",
            "SVM Precision Score =  100.0 %\n",
            "SVM Recall Score =  93.54838709677419 %\n",
            "SVM f1 Score =  96.66666666666666 %\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# EVALUASI VALIDASI K-FOLD CROSS VALIDATION"
      ],
      "metadata": {
        "id": "q-sl4cKiZ49x"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import cross_val_predict\n",
        "from sklearn.model_selection import cross_val_score\n",
        "#10 FOLD\n",
        "scores_test = cross_val_score(svm, Test_X_Tfidf, Test_Y, cv = 10)\n",
        "print(\"Hasil Akurasi menggunakan 10 Fold Cross Validation \\n\")\n",
        "for i in range(10):\n",
        "    print(\"Akurasi dari SVM Iterasi ke -\", i+1, \"  : {0:2}\".format(scores_test[i,]*100))\n",
        "print(\"\\n\",\"Rata-Rata Akurasi dari SVM menggunakan Cross Validation :\", scores_test.mean()*100)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Dxw4qppjZ-cn",
        "outputId": "5ff928ba-cb92-4b45-b1d1-925e708b0d8a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Hasil Akurasi menggunakan 10 Fold Cross Validation \n",
            "\n",
            "Akurasi dari SVM Iterasi ke - 1   : 90.9090909090909\n",
            "Akurasi dari SVM Iterasi ke - 2   : 95.45454545454545\n",
            "Akurasi dari SVM Iterasi ke - 3   : 86.36363636363636\n",
            "Akurasi dari SVM Iterasi ke - 4   : 90.9090909090909\n",
            "Akurasi dari SVM Iterasi ke - 5   : 81.81818181818183\n",
            "Akurasi dari SVM Iterasi ke - 6   : 95.45454545454545\n",
            "Akurasi dari SVM Iterasi ke - 7   : 95.45454545454545\n",
            "Akurasi dari SVM Iterasi ke - 8   : 86.36363636363636\n",
            "Akurasi dari SVM Iterasi ke - 9   : 85.71428571428571\n",
            "Akurasi dari SVM Iterasi ke - 10   : 95.23809523809523\n",
            "\n",
            " Rata-Rata Akurasi dari SVM menggunakan Cross Validation : 90.36796536796538\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#10 FOLD - Precission\n",
        "\n",
        "scores_test = cross_val_score(svm_tuned, Test_X_Tfidf, Test_Y, cv = 10, scoring='precision')\n",
        "scores_test\n",
        "print(\"Hasil Presisi menggunakan 10 Fold Cross Validation \\n\")\n",
        "for i in range(10):\n",
        "    print(\"Presisi dari SVM Iterasi ke -\", i+1, \"  : {0:2}\".format(scores_test[i,]*100))\n",
        "print(\"\\n\",\"Rata-Rata Presisi dari SVM menggunakan Cross Validation :\", scores_test.mean()*100)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GeTnqzlxaC0j",
        "outputId": "a9e6f912-1811-4a6c-ff16-3b28099e78bd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Hasil Presisi menggunakan 10 Fold Cross Validation \n",
            "\n",
            "Presisi dari SVM Iterasi ke - 1   : 93.33333333333333\n",
            "Presisi dari SVM Iterasi ke - 2   : 100.0\n",
            "Presisi dari SVM Iterasi ke - 3   : 87.5\n",
            "Presisi dari SVM Iterasi ke - 4   : 87.5\n",
            "Presisi dari SVM Iterasi ke - 5   : 85.71428571428571\n",
            "Presisi dari SVM Iterasi ke - 6   : 93.33333333333333\n",
            "Presisi dari SVM Iterasi ke - 7   : 93.33333333333333\n",
            "Presisi dari SVM Iterasi ke - 8   : 92.3076923076923\n",
            "Presisi dari SVM Iterasi ke - 9   : 86.66666666666667\n",
            "Presisi dari SVM Iterasi ke - 10   : 100.0\n",
            "\n",
            " Rata-Rata Presisi dari SVM menggunakan Cross Validation : 91.96886446886448\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#10 FOLD - Recall\n",
        "\n",
        "scores_test = cross_val_score(svm_tuned, Test_X_Tfidf, Test_Y, cv = 10, scoring='recall')\n",
        "scores_test\n",
        "print(\"Hasil Recall menggunakan 10 Fold Cross Validation \\n\")\n",
        "for i in range(10):\n",
        "    print(\"Recall dari SVM Iterasi ke -\", i+1, \"  : {0:2}\".format(scores_test[i,]*100))\n",
        "print(\"\\n\",\"Rata-Rata Recall dari SVM menggunakan Cross Validation :\", scores_test.mean()*100)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LzkuDYibaFwr",
        "outputId": "8923107c-7a12-4e59-d09a-7d35e768f153"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Hasil Recall menggunakan 10 Fold Cross Validation \n",
            "\n",
            "Recall dari SVM Iterasi ke - 1   : 93.33333333333333\n",
            "Recall dari SVM Iterasi ke - 2   : 93.33333333333333\n",
            "Recall dari SVM Iterasi ke - 3   : 93.33333333333333\n",
            "Recall dari SVM Iterasi ke - 4   : 100.0\n",
            "Recall dari SVM Iterasi ke - 5   : 85.71428571428571\n",
            "Recall dari SVM Iterasi ke - 6   : 100.0\n",
            "Recall dari SVM Iterasi ke - 7   : 100.0\n",
            "Recall dari SVM Iterasi ke - 8   : 85.71428571428571\n",
            "Recall dari SVM Iterasi ke - 9   : 92.85714285714286\n",
            "Recall dari SVM Iterasi ke - 10   : 100.0\n",
            "\n",
            " Rata-Rata Recall dari SVM menggunakan Cross Validation : 94.42857142857143\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#10 FOLD - F1 SCORE\n",
        "\n",
        "scores_test = cross_val_score(svm_tuned, Test_X_Tfidf, Test_Y, cv = 10, scoring='f1')\n",
        "scores_test\n",
        "print(\"Hasil F1 Score menggunakan 10 Fold Cross Validation \\n\")\n",
        "for i in range(10):\n",
        "    print(\"F1 Score dari SVM Iterasi ke -\", i+1, \"  : {0:2}\".format(scores_test[i,]*100))\n",
        "print(\"\\n\",\"Rata-Rata F1 Score dari SVM menggunakan Cross Validation :\", scores_test.mean()*100)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3dtWulSRaISs",
        "outputId": "00df36cb-b282-4ff0-ad26-4e4784f8ca08"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Hasil F1 Score menggunakan 10 Fold Cross Validation \n",
            "\n",
            "F1 Score dari SVM Iterasi ke - 1   : 93.33333333333333\n",
            "F1 Score dari SVM Iterasi ke - 2   : 96.55172413793103\n",
            "F1 Score dari SVM Iterasi ke - 3   : 90.32258064516128\n",
            "F1 Score dari SVM Iterasi ke - 4   : 93.33333333333333\n",
            "F1 Score dari SVM Iterasi ke - 5   : 85.71428571428571\n",
            "F1 Score dari SVM Iterasi ke - 6   : 96.55172413793103\n",
            "F1 Score dari SVM Iterasi ke - 7   : 96.55172413793103\n",
            "F1 Score dari SVM Iterasi ke - 8   : 88.8888888888889\n",
            "F1 Score dari SVM Iterasi ke - 9   : 89.65517241379311\n",
            "F1 Score dari SVM Iterasi ke - 10   : 100.0\n",
            "\n",
            " Rata-Rata F1 Score dari SVM menggunakan Cross Validation : 93.09027667425887\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def classify(tweet):\n",
        "    pred = svm.predict(Tfidf_vect.transform([tweet]))\n",
        "    if pred == 1:\n",
        "        return \"Positif\"\n",
        "    return \"Negatif\""
      ],
      "metadata": {
        "id": "Pv1VjNenaL_a"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "classify('IKN akan jadi representasi bangsa yang unggul')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "jQnYUJiQaOyS",
        "outputId": "856c5a73-390b-4489-cbec-44ac43515ea4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Positif'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 80
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "classify('IKN memberikan dampak positif')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "nRwieB3ZaQ_G",
        "outputId": "9b4632b9-c484-4375-f9dc-275d9a095e87"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Positif'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "classify('proyek bengkak')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "SZ_ZYaxiaUnc",
        "outputId": "ebe45c5b-5875-488f-a003-fad84c0c0c6a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Negatif'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 82
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "classify('IKN proyek gagal')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "FZwVMOWBaWng",
        "outputId": "b25d7d58-db8b-4300-a320-4c2f1a166ccf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Negatif'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "classify('mari kita dukung pembangunan IKN')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "L-ldwSNDaY6c",
        "outputId": "286b6c6c-15a6-445b-e99c-bd4c50f84c36"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Positif'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 84
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "classify('IKN bangkitkan ekonomi Indonesia')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "p3MJ_Qwwabcr",
        "outputId": "03539a56-3286-444d-ed96-73efa51cc74d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Positif'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 85
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "classify('IKN kota dunia untuk semua')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "a-_U_XJJadkj",
        "outputId": "4c523a13-2e73-4f40-87bb-c41f2d0d5e2e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Positif'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 87
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "classify('menuju Indonesia maju dan berkembang')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "1bmYdhR4ahYk",
        "outputId": "b2ed6ffc-402a-4759-c168-fbc9ae78d421"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Positif'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 86
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "classify('pusat ekonomi masa depan')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "h5gWGnunajrc",
        "outputId": "4cff3e7b-1400-414b-b929-d9eb8de21cab"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Positif'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 88
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "classify('forest city')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "8m4mcJjGamNR",
        "outputId": "713a5721-4408-4846-b1e0-c9318f63e23c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Positif'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 89
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "classify('konsep Green City')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "Y08cxPRhaoQN",
        "outputId": "731662fb-7db3-4577-8b39-d60bcbb3e870"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Positif'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 90
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "classify('investor ragu tanam modal')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "ULsBxdKPaq8K",
        "outputId": "19af88f7-d0fd-4052-9215-95b003f0127b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Negatif'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 91
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "classify('IKN lebih penting dari entaskan kemiskinan')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "kqhzhjbwgf5F",
        "outputId": "9351544b-0b06-44bf-ea1b-1b1df0f7245a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Negatif'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 94
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "classify('curiga IKN')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "XX8HAYm9il2E",
        "outputId": "d2b49918-12a1-4a94-b778-2882d8473640"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Negatif'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 98
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#STEMMING\n",
        "# create stemmer\n",
        "factory = StemmerFactory()\n",
        "stemming = factory.create_stemmer()\n",
        "# Using a Python list comprehension method to apply to all words in my_list\n",
        "def stem(text):\n",
        "    my_list = text\n",
        "    stemmed_list = [stemming.stem(word) for word in my_list]\n",
        "    return (stemmed_list)"
      ],
      "metadata": {
        "id": "1Kwm8sgcatmp"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def preprocess(text):\n",
        "    text = cleansing(text)\n",
        "    text = case_folding(text)\n",
        "    text = tokenization(text)\n",
        "    text = stopwords_removal(text)\n",
        "    text = stem(text)\n",
        "    text = normalized_term(text)\n",
        "    text = fit_normalisasi(text)\n",
        "    text = convert_negasi(text)\n",
        "    return text"
      ],
      "metadata": {
        "id": "383JfEpaavzv"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "a= preprocess('Dukung pembangunan IKN di Kalimantan Timur https/twitter.com #dukungIKN')\n",
        "a"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "lXxAlw3zayBL",
        "outputId": "dbfb9a63-7e41-4156-d724-1b9d000ccbe3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'dukung bangun ikn kalimantan timur dukungikn'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 102
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "classify(a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "OqjAbzu6a0su",
        "outputId": "b3192c65-4134-4d5d-ae9c-b4831b029657"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Positif'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 103
        }
      ]
    }
  ]
}