{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"authorship_tag":"ABX9TyPedIjNvWRqslt7Z04vVVfz"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"code","execution_count":62,"metadata":{"id":"j3SSvcNGPcd6","executionInfo":{"status":"ok","timestamp":1761566327673,"user_tz":-420,"elapsed":5,"user":{"displayName":"NICHOLAS DANIARDI","userId":"13862910458135710281"}}},"outputs":[],"source":["import pandas as pd\n","import numpy as np\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","from sklearn.model_selection import train_test_split, GridSearchCV, RandomizedSearchCV\n","from sklearn.preprocessing import StandardScaler, OneHotEncoder, LabelEncoder\n","from sklearn.compose import ColumnTransformer\n","from sklearn.pipeline import Pipeline\n","from sklearn.metrics import classification_report, accuracy_score, confusion_matrix\n","from sklearn.ensemble import RandomForestClassifier\n","import xgboost as xgb\n","from io import StringIO"]},{"cell_type":"markdown","source":["# Initialize Dataset"],"metadata":{"id":"M0n4BGOqQWJI"}},{"cell_type":"code","source":["nama_file = \"data_anak_stunting_temanggung.csv\"\n","try:\n","    df = pd.read_csv(nama_file)\n","    print(f\"\\n==== 2. Inisialisasi Dataset '{nama_file}' Berhasil ====\")\n","    print(\"\\n==== Info Awal Dataset g====\")\n","    buffer = StringIO()\n","    df.info(buf=buffer)\n","    print(buffer.getvalue())\n","    print(\"\\n==== 5 Baris Teratas Data Awal ====\")\n","    print(df.head())\n","except FileNotFoundError:\n","    print(f\"File '{nama_file}' tidak ditemukan. Harap unggah file tersebut ke Google Colab.\")\n","except Exception as e:\n","    print(f\"Terjadi error saat membaca file: {e}\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"UaKU-0Y1Qbxh","executionInfo":{"status":"ok","timestamp":1761566327705,"user_tz":-420,"elapsed":28,"user":{"displayName":"NICHOLAS DANIARDI","userId":"13862910458135710281"}},"outputId":"60e30b50-1bc4-451d-e756-f85abc7bf8eb"},"execution_count":63,"outputs":[{"output_type":"stream","name":"stdout","text":["\n","==== 2. Inisialisasi Dataset 'data_anak_stunting_temanggung.csv' Berhasil ====\n","\n","==== Info Awal Dataset g====\n","<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 2200 entries, 0 to 2199\n","Data columns (total 12 columns):\n"," #   Column              Non-Null Count  Dtype  \n","---  ------              --------------  -----  \n"," 0   id                  2200 non-null   int64  \n"," 1   jenis_data          2200 non-null   object \n"," 2   id_anak             2200 non-null   object \n"," 3   jenis_kelamin       2200 non-null   object \n"," 4   tanggal_lahir       2200 non-null   object \n"," 5   tanggal_pengukuran  2200 non-null   object \n"," 6   usia_bulan          2200 non-null   float64\n"," 7   tinggi_badan_cm     2200 non-null   float64\n"," 8   skor_z_haz          2200 non-null   float64\n"," 9   status_stunting     2200 non-null   object \n"," 10  kecamatan           2200 non-null   object \n"," 11  desa                2200 non-null   object \n","dtypes: float64(3), int64(1), object(8)\n","memory usage: 206.4+ KB\n","\n","\n","==== 5 Baris Teratas Data Awal ====\n","   id jenis_data id_anak jenis_kelamin tanggal_lahir tanggal_pengukuran  \\\n","0   1       Anak   A0001     Perempuan     5/29/2025          10/1/2025   \n","1   2       Anak   A0002     Laki-laki     6/17/2024          10/1/2025   \n","2   3       Anak   A0003     Perempuan     9/12/2023          10/1/2025   \n","3   4       Anak   A0004     Laki-laki    10/17/2024          10/1/2025   \n","4   5       Anak   A0005     Laki-laki     4/29/2023          10/1/2025   \n","\n","   usia_bulan  tinggi_badan_cm  skor_z_haz  status_stunting kecamatan  \\\n","0         4.1             52.1       -2.32  Stunting Ringan  Gemawang   \n","1        15.5             79.5       -2.56  Stunting Ringan  Gemawang   \n","2        24.6            105.9       -0.73           Normal  Gemawang   \n","3        11.5             73.3        0.91           Normal  Gemawang   \n","4        29.1            113.2       -0.77           Normal  Gemawang   \n","\n","        desa  \n","0  Tlogorejo  \n","1  Ngadisepi  \n","2     Losari  \n","3  Ngadisepi  \n","4     Losari  \n"]}]},{"cell_type":"markdown","source":["# exploratory data analysis (EDA)"],"metadata":{"id":"WLlE8T1GQfdB"}},{"cell_type":"code","source":["print(\"\\n==== Informasi Dataset ====\")\n","print(df.info())"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"2D_eXuMsQrmK","executionInfo":{"status":"ok","timestamp":1761566327724,"user_tz":-420,"elapsed":18,"user":{"displayName":"NICHOLAS DANIARDI","userId":"13862910458135710281"}},"outputId":"6c0125cf-11b2-476b-f540-d68a2de47fdc"},"execution_count":64,"outputs":[{"output_type":"stream","name":"stdout","text":["\n","==== Informasi Dataset ====\n","<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 2200 entries, 0 to 2199\n","Data columns (total 12 columns):\n"," #   Column              Non-Null Count  Dtype  \n","---  ------              --------------  -----  \n"," 0   id                  2200 non-null   int64  \n"," 1   jenis_data          2200 non-null   object \n"," 2   id_anak             2200 non-null   object \n"," 3   jenis_kelamin       2200 non-null   object \n"," 4   tanggal_lahir       2200 non-null   object \n"," 5   tanggal_pengukuran  2200 non-null   object \n"," 6   usia_bulan          2200 non-null   float64\n"," 7   tinggi_badan_cm     2200 non-null   float64\n"," 8   skor_z_haz          2200 non-null   float64\n"," 9   status_stunting     2200 non-null   object \n"," 10  kecamatan           2200 non-null   object \n"," 11  desa                2200 non-null   object \n","dtypes: float64(3), int64(1), object(8)\n","memory usage: 206.4+ KB\n","None\n"]}]},{"cell_type":"markdown","source":["# Visualisasi Data"],"metadata":{"id":"xaKNaFfWZGkV"}},{"cell_type":"code","source":["sns.countplot(x='status_stunting', data=df)\n","plt.title('Distribusi Status Stunting')\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":480},"id":"Owq8ufq2ZJt4","executionInfo":{"status":"ok","timestamp":1761566327912,"user_tz":-420,"elapsed":186,"user":{"displayName":"NICHOLAS DANIARDI","userId":"13862910458135710281"}},"outputId":"0dd6dbc5-1681-43e8-e557-ad2de495b85f"},"execution_count":65,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["sns.countplot(x='jenis_kelamin', hue='status_stunting', data=df)\n","plt.title('Status Stunting Berdasarkan Jenis Kelamin')\n","plt.show()\n","\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":480},"id":"CRhCgwL7ZUWU","executionInfo":{"status":"ok","timestamp":1761566328095,"user_tz":-420,"elapsed":179,"user":{"displayName":"NICHOLAS DANIARDI","userId":"13862910458135710281"}},"outputId":"05075ab1-e3ff-4139-bc3b-e37c8099610e"},"execution_count":66,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["sns.histplot(df['tinggi_badan_cm'], kde=True)\n","plt.title('Distribusi Tinggi Badan (cm)')\n","plt.show()\n","\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":480},"id":"gc62-s-zZZrK","executionInfo":{"status":"ok","timestamp":1761566328369,"user_tz":-420,"elapsed":272,"user":{"displayName":"NICHOLAS DANIARDI","userId":"13862910458135710281"}},"outputId":"acda221e-111d-4563-a12f-1d0e1a25c56c"},"execution_count":67,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["sns.heatmap(df.corr(numeric_only=True), annot=True, cmap='coolwarm')\n","plt.title('Heatmap Korelasi Variabel Numerik')\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":572},"id":"5jNxyu2RZcD6","executionInfo":{"status":"ok","timestamp":1761566328579,"user_tz":-420,"elapsed":208,"user":{"displayName":"NICHOLAS DANIARDI","userId":"13862910458135710281"}},"outputId":"5b5d47c1-08b4-4d3f-bafb-e5686430dd09"},"execution_count":68,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["# Data Processing"],"metadata":{"id":"6XexxRXKQv5l"}},{"cell_type":"code","source":["print(\"\\n==== 4. Pemrosesan Data (Memilih Fitur & Membuang yang Tidak Perlu) ====\")\n","\n","print(\"\\n==== Menerapkan Konversi Tipe Data ====\")\n","if 'tanggal_lahir' in df.columns:\n","    df['tanggal_lahir'] = pd.to_datetime(df['tanggal_lahir'], errors='coerce')\n","if 'tanggal_pengukuran' in df.columns:\n","    df['tanggal_pengukuran'] = pd.to_datetime(df['tanggal_pengukuran'], errors='coerce')\n","\n","kategori_cols = ['jenis_data', 'id_anak', 'jenis_kelamin', 'status_stunting', 'kecamatan', 'desa']\n","for col in kategori_cols:\n","    if col in df.columns:\n","        df[col] = df[col].astype('category')\n","\n","print(\"\\n==== Informasi Dataset Setelah Mengubah Data Type ====\")\n","buffer_post = StringIO()\n","df.info(buf=buffer_post)\n","print(buffer_post.getvalue())\n","\n","\n","\n","features_to_use = ['usia_bu.lan', 'tinggi_badan_cm', 'jenis_kelamin']\n","target_col = 'status_stunting'\n","\n","if not all(col in df.columns for col in features_to_use + [target_col]):\n","    print(f\"Error: Tidak semua kolom {features_to_use + [target_col]} ada di DataFrame.\")\n","else:\n","    target_categories = ['Normal', 'Stunting Ringan', 'Stunting Berat']\n","\n","    df_model = df[features_to_use + [target_col]].copy()\n","\n","    print(f\"\\nMemfilter data untuk target: {target_categories}\")\n","    df_model = df_model[df_model[target_col].isin(target_categories)]\n","    df_model[target_col] = df_model[target_col].cat.remove_unused_categories()\n","\n","    print(f\"\\nJumlah data sebelum dropna: {len(df_model)}\")\n","    df_model.dropna(inplace=True)\n","    print(f\"Jumlah data setelah dropna: {len(df_model)}\")\n","\n","    print(f\"\\nDistribusi target setelah difilter dan dibersihkan:\")\n","    print(df_model[target_col].value_counts())"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"qXfMkstXQ3Rr","executionInfo":{"status":"ok","timestamp":1761566328598,"user_tz":-420,"elapsed":23,"user":{"displayName":"NICHOLAS DANIARDI","userId":"13862910458135710281"}},"outputId":"aa5abfea-051f-481f-ce2c-49add32a4bbd"},"execution_count":69,"outputs":[{"output_type":"stream","name":"stdout","text":["\n","==== 4. Pemrosesan Data (Memilih Fitur & Membuang yang Tidak Perlu) ====\n","\n","==== Menerapkan Konversi Tipe Data ====\n","\n","==== Informasi Dataset Setelah Mengubah Data Type ====\n","<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 2200 entries, 0 to 2199\n","Data columns (total 12 columns):\n"," #   Column              Non-Null Count  Dtype         \n","---  ------              --------------  -----         \n"," 0   id                  2200 non-null   int64         \n"," 1   jenis_data          2200 non-null   category      \n"," 2   id_anak             2200 non-null   category      \n"," 3   jenis_kelamin       2200 non-null   category      \n"," 4   tanggal_lahir       2200 non-null   datetime64[ns]\n"," 5   tanggal_pengukuran  2200 non-null   datetime64[ns]\n"," 6   usia_bulan          2200 non-null   float64       \n"," 7   tinggi_badan_cm     2200 non-null   float64       \n"," 8   skor_z_haz          2200 non-null   float64       \n"," 9   status_stunting     2200 non-null   category      \n"," 10  kecamatan           2200 non-null   category      \n"," 11  desa                2200 non-null   category      \n","dtypes: category(6), datetime64[ns](2), float64(3), int64(1)\n","memory usage: 201.5 KB\n","\n","\n","Memfilter data untuk target: ['Normal', 'Stunting Ringan', 'Stunting Berat']\n","\n","Jumlah data sebelum dropna: 2200\n","Jumlah data setelah dropna: 2200\n","\n","Distribusi target setelah difilter dan dibersihkan:\n","status_stunting\n","Normal             1727\n","Stunting Ringan     359\n","Stunting Berat      114\n","Name: count, dtype: int64\n"]}]},{"cell_type":"markdown","source":["# Menghapus Kolom Yang Tidak Diperlukan"],"metadata":{"id":"-K32L69BZnD1"}},{"cell_type":"code","source":["df = df.drop(['id', 'id_anak', 'tanggal_lahir', 'tanggal_pengukuran'], axis=1, errors='ignore')\n","print(df.columns.tolist())\n","print(df.head())"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"0lW_5FkkZrGE","executionInfo":{"status":"ok","timestamp":1761566328619,"user_tz":-420,"elapsed":20,"user":{"displayName":"NICHOLAS DANIARDI","userId":"13862910458135710281"}},"outputId":"fdbcf5f8-20c9-4761-d532-4f6bfad8b9f4"},"execution_count":70,"outputs":[{"output_type":"stream","name":"stdout","text":["['jenis_data', 'jenis_kelamin', 'usia_bulan', 'tinggi_badan_cm', 'skor_z_haz', 'status_stunting', 'kecamatan', 'desa']\n","  jenis_data jenis_kelamin  usia_bulan  tinggi_badan_cm  skor_z_haz  \\\n","0       Anak     Perempuan         4.1             52.1       -2.32   \n","1       Anak     Laki-laki        15.5             79.5       -2.56   \n","2       Anak     Perempuan        24.6            105.9       -0.73   \n","3       Anak     Laki-laki        11.5             73.3        0.91   \n","4       Anak     Laki-laki        29.1            113.2       -0.77   \n","\n","   status_stunting kecamatan       desa  \n","0  Stunting Ringan  Gemawang  Tlogorejo  \n","1  Stunting Ringan  Gemawang  Ngadisepi  \n","2           Normal  Gemawang     Losari  \n","3           Normal  Gemawang  Ngadisepi  \n","4           Normal  Gemawang     Losari  \n"]}]},{"cell_type":"markdown","source":["# Splitting Data"],"metadata":{"id":"o4e5x5c-Q6cp"}},{"cell_type":"code","source":["print(\"\\n==== 5. Pemisahan Data (Mentah) ====\")\n","if 'df_model' in locals() and not df_model.empty:\n","    X = df_model[features_to_use]\n","    y = df_model[target_col]\n","    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42, stratify=y)\n","    print(f\"Ukuran data latih (X_train mentah): {X_train.shape}\")\n","    print(f\"Ukuran data uji (X_test mentah): {X_test.shape}\")\n","else:\n","    print(\"Error: 'df_model' tidak terdefinisi atau kosong. Jalankan blok 4 terlebih dahulu.\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"8p2RMYMRQ_Lr","executionInfo":{"status":"ok","timestamp":1761566328639,"user_tz":-420,"elapsed":18,"user":{"displayName":"NICHOLAS DANIARDI","userId":"13862910458135710281"}},"outputId":"4479b080-b839-4ef1-d87b-605cdd3d0e74"},"execution_count":71,"outputs":[{"output_type":"stream","name":"stdout","text":["\n","==== 5. Pemisahan Data (Mentah) ====\n","Ukuran data latih (X_train mentah): (1760, 3)\n","Ukuran data uji (X_test mentah): (440, 3)\n"]}]},{"cell_type":"markdown","source":["# Encode"],"metadata":{"id":"78SM6RMeRCK6"}},{"cell_type":"code","source":["data_jk = df['jenis_kelamin']\n","encoder = LabelEncoder()\n","\n","encode_jk = encoder.fit_transform(data_jk)\n","df_encoded = df.copy()\n","df_encoded['jenis_kelamin'] = encode_jk\n","# 1 = Perempuan\n","# 0 = Laki-laki\n","\n","display(df_encoded.head())"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"WJ9C3gO_REZS","executionInfo":{"status":"ok","timestamp":1761567733495,"user_tz":-420,"elapsed":65,"user":{"displayName":"NICHOLAS DANIARDI","userId":"13862910458135710281"}},"outputId":"27ec5688-9aae-4a9e-b1f6-d2b24a919bc8"},"execution_count":79,"outputs":[{"output_type":"display_data","data":{"text/plain":["  jenis_data  jenis_kelamin  usia_bulan  tinggi_badan_cm  skor_z_haz  \\\n","0       Anak              1         4.1             52.1       -2.32   \n","1       Anak              0        15.5             79.5       -2.56   \n","2       Anak              1        24.6            105.9       -0.73   \n","3       Anak              0        11.5             73.3        0.91   \n","4       Anak              0        29.1            113.2       -0.77   \n","\n","   status_stunting kecamatan       desa  \n","0  Stunting Ringan  Gemawang  Tlogorejo  \n","1  Stunting Ringan  Gemawang  Ngadisepi  \n","2           Normal  Gemawang     Losari  \n","3           Normal  Gemawang  Ngadisepi  \n","4           Normal  Gemawang     Losari  "],"text/html":["\n","  <div id=\"df-d6e92788-dac6-4524-a2fc-54812b30d5e1\" 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>jenis_data</th>\n","      <th>jenis_kelamin</th>\n","      <th>usia_bulan</th>\n","      <th>tinggi_badan_cm</th>\n","      <th>skor_z_haz</th>\n","      <th>status_stunting</th>\n","      <th>kecamatan</th>\n","      <th>desa</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>Anak</td>\n","      <td>1</td>\n","      <td>4.1</td>\n","      <td>52.1</td>\n","      <td>-2.32</td>\n","      <td>Stunting Ringan</td>\n","      <td>Gemawang</td>\n","      <td>Tlogorejo</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>Anak</td>\n","      <td>0</td>\n","      <td>15.5</td>\n","      <td>79.5</td>\n","      <td>-2.56</td>\n","      <td>Stunting Ringan</td>\n","      <td>Gemawang</td>\n","      <td>Ngadisepi</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>Anak</td>\n","      <td>1</td>\n","      <td>24.6</td>\n","      <td>105.9</td>\n","      <td>-0.73</td>\n","      <td>Normal</td>\n","      <td>Gemawang</td>\n","      <td>Losari</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>Anak</td>\n","      <td>0</td>\n","      <td>11.5</td>\n","      <td>73.3</td>\n","      <td>0.91</td>\n","      <td>Normal</td>\n","      <td>Gemawang</td>\n","      <td>Ngadisepi</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>Anak</td>\n","      <td>0</td>\n","      <td>29.1</td>\n","      <td>113.2</td>\n","      <td>-0.77</td>\n","      <td>Normal</td>\n","      <td>Gemawang</td>\n","      <td>Losari</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d6e92788-dac6-4524-a2fc-54812b30d5e1')\"\n","            title=\"Convert this dataframe to an 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Model 1: Random Forest Unoptimized ====\")\n","\n","rf_unoptimized = RandomForestClassifier(random_state=42)\n","\n","rf_unoptimized.fit(X_train_processed, y_train_encoded)\n","\n","y_pred_rf_un = rf_unoptimized.predict(X_test_processed)\n","\n","\n","acc_rf_un = accuracy_score(y_test_encoded, y_pred_rf_un)\n","print(\"=== Random Forest (Unoptimized) ===\")\n","print(\"Akurasi:\", acc_rf_un)\n","\n","print(classification_report(y_test_encoded, y_pred_rf_un, target_names=list(le.classes_)))\n","\n","plt.figure(figsize=(5,4))\n","\n","sns.heatmap(confusion_matrix(y_test_encoded, y_pred_rf_un), annot=True, fmt='d', cmap='Blues',\n","            xticklabels=le.classes_, yticklabels=le.classes_)\n","plt.title(\"Confusion Matrix - RF (Unoptimized)\")\n","plt.xlabel(\"Predicted\")\n","plt.ylabel(\"Actual\")\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":769},"id":"e0p7gNDSRL0R","executionInfo":{"status":"ok","timestamp":1761566329318,"user_tz":-420,"elapsed":596,"user":{"displayName":"NICHOLAS DANIARDI","userId":"13862910458135710281"}},"outputId":"7ce21b37-ff3b-406c-88bf-5938a88cede6"},"execution_count":74,"outputs":[{"output_type":"stream","name":"stdout","text":["\n","==== 7. Model 1: Random Forest Unoptimized ====\n","=== Random Forest (Unoptimized) ===\n","Akurasi: 0.7318181818181818\n","                 precision    recall  f1-score   support\n","\n","         Normal       0.80      0.91      0.85       345\n"," Stunting Berat       0.00      0.00      0.00        23\n","Stunting Ringan       0.21      0.12      0.16        72\n","\n","       accuracy                           0.73       440\n","      macro avg       0.34      0.34      0.34       440\n","   weighted avg       0.66      0.73      0.69       440\n","\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 500x400 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["print(\"\\n==== 8. Model 2: Random Forest GridSearch (Tuned) ====\")\n","print(\"Memulai GridSearchCV... Ini mungkin memakan waktu beberapa menit.\")\n","\n","param_grid = {\n","    'n_estimators': [100, 200, 300],\n","    'max_depth': [10, 20, None],\n","    'min_samples_split': [2, 5, 10],\n","    'min_samples_leaf': [1, 2, 4],\n","    'max_features': ['sqrt', 'log2']\n","}\n","\n","grid_rf = GridSearchCV(\n","    estimator=RandomForestClassifier(random_state=42),\n","    param_grid=param_grid,\n","    scoring='accuracy',\n","    cv=3,\n","    n_jobs=-1,\n","    verbose=2\n",")\n","\n","\n","grid_rf.fit(X_train_processed, y_train_encoded)\n","\n","print(\"Tuning Selesai.\")\n","best_rf = grid_rf.best_estimator_\n","\n","y_pred_rf_best = best_rf.predict(X_test_processed)\n","\n","acc_rf_best = accuracy_score(y_test_encoded, y_pred_rf_best)\n","\n","print(\"\\n=== Random Forest (Grid Search) ===\")\n","print(\"Best Params:\", grid_rf.best_params_)\n","print(\"Akurasi:\", acc_rf_best)\n","\n","print(classification_report(y_test_encoded, y_pred_rf_best, target_names=[str(c) for c in le.classes_]))\n","\n","plt.figure(figsize=(5, 4))\n","sns.heatmap(confusion_matrix(y_test_encoded, y_pred_rf_best), annot=True, fmt='d', cmap='Greens',\n","            xticklabels=[str(c) for c in le.classes_],\n","            yticklabels=[str(c) for c in le.classes_])\n","plt.title(\"Confusion Matrix - RF (Optimized)\")\n","plt.xlabel(\"Predicted\")\n","plt.ylabel(\"Actual\")\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":980},"id":"Ve2m_ZVTTyzb","executionInfo":{"status":"ok","timestamp":1761566605054,"user_tz":-420,"elapsed":275734,"user":{"displayName":"NICHOLAS DANIARDI","userId":"13862910458135710281"}},"outputId":"2ba93469-07fb-4d8e-e700-6179327efc78"},"execution_count":75,"outputs":[{"output_type":"stream","name":"stdout","text":["\n","==== 8. Model 2: Random Forest GridSearch (Tuned) ====\n","Memulai GridSearchCV... Ini mungkin memakan waktu beberapa menit.\n","Fitting 3 folds for each of 162 candidates, totalling 486 fits\n","Tuning Selesai.\n","\n","=== Random Forest (Grid Search) ===\n","Best Params: {'max_depth': 10, 'max_features': 'sqrt', 'min_samples_leaf': 4, 'min_samples_split': 2, 'n_estimators': 100}\n","Akurasi: 0.7840909090909091\n","                 precision    recall  f1-score   support\n","\n","         Normal       0.78      1.00      0.88       345\n"," Stunting Berat       0.00      0.00      0.00        23\n","Stunting Ringan       0.00      0.00      0.00        72\n","\n","       accuracy                           0.78       440\n","      macro avg       0.26      0.33      0.29       440\n","   weighted avg       0.61      0.78      0.69       440\n","\n"]},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.12/dist-packages/sklearn/metrics/_classification.py:1565: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n","  _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n","/usr/local/lib/python3.12/dist-packages/sklearn/metrics/_classification.py:1565: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n","  _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n","/usr/local/lib/python3.12/dist-packages/sklearn/metrics/_classification.py:1565: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n","  _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 500x400 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["# ====================================================================\n","# BLOK 9: MODEL 3 - XGBOOST (TUNED)\n","# ====================================================================\n","\n","print(\"\\n==== 9. Model 3: XGBoost (Tuned dengan RandomizedSearch) ====\")\n","print(\"Memulai RandomizedSearchCV... Ini mungkin memakan waktu.\")\n","\n","try:\n","\n","    xgb_model = xgb.XGBClassifier(\n","        objective='multi:softmax',\n","        num_class=len(le.classes_),\n","        eval_metric='mlogloss',\n","        use_label_encoder=False,\n","        random_state=42\n","    )\n","\n","    param_dist = {\n","        'n_estimators': [100, 200, 300],\n","        'max_depth': [3, 5, 7],\n","        'learning_rate': [0.01, 0.05, 0.1],\n","        'subsample': [0.7, 1.0],\n","        'colsample_bytree': [0.7, 1.0],\n","    }\n","\n","    random_xgb = RandomizedSearchCV(\n","        estimator=xgb_model,\n","        param_distributions=param_dist,\n","        n_iter=20,\n","        scoring='accuracy',\n","        cv=3,\n","        random_state=42,\n","        n_jobs=-1,\n","        verbose=2\n","    )\n","\n","    random_xgb.fit(X_train_processed, y_train_encoded)\n","\n","    print(\"Tuning Selesai.\")\n","    best_xgb = random_xgb.best_estimator_\n","\n","    y_pred_xgb = best_xgb.predict(X_test_processed)\n","\n","    acc_xgb = accuracy_score(y_test_encoded, y_pred_xgb)\n","    print(\"\\n=== XGBoost (Tuned) ===\")\n","    print(\"Best Params:\", random_xgb.best_params_)\n","    print(\"Akurasi:\", acc_xgb)\n","\n","    print(classification_report(y_test_encoded, y_pred_xgb, target_names=[str(c) for c in le.classes_]))\n","\n","    plt.figure(figsize=(5,4))\n","\n","    sns.heatmap(confusion_matrix(y_test_encoded, y_pred_xgb), annot=True, fmt='d', cmap='Oranges',\n","                xticklabels=[str(c) for c in le.classes_],\n","                yticklabels=[str(c) for c in le.classes_])\n","    plt.title(\"Confusion Matrix - XGBoost (Tuned)\")\n","    plt.xlabel(\"Predicted\")\n","    plt.ylabel(\"Actual\")\n","    plt.show()\n","\n","except NameError as e:\n","    print(f\"\\nERROR: Terjadi NameError. Kemungkinan besar Anda belum menjalankan Blok 6.\")\n","    print(f\"Pesan Error: {e}\")\n","except Exception as e:\n","    print(f\"\\nTerjadi Error: {e}\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"mZRSwdPlT1hW","executionInfo":{"status":"ok","timestamp":1761566617983,"user_tz":-420,"elapsed":12926,"user":{"displayName":"NICHOLAS DANIARDI","userId":"13862910458135710281"}},"outputId":"00cd3d32-e57f-49ed-a959-66b30142bf3f"},"execution_count":76,"outputs":[{"output_type":"stream","name":"stdout","text":["\n","==== 9. Model 3: XGBoost (Tuned dengan RandomizedSearch) ====\n","Memulai RandomizedSearchCV... Ini mungkin memakan waktu.\n","Fitting 3 folds for each of 20 candidates, totalling 60 fits\n"]},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.12/dist-packages/xgboost/training.py:199: UserWarning: [12:02:36] WARNING: /workspace/src/learner.cc:790: \n","Parameters: { \"use_label_encoder\" } are not used.\n","\n","  bst.update(dtrain, iteration=i, fobj=obj)\n"]},{"output_type":"stream","name":"stdout","text":["Tuning Selesai.\n","\n","=== XGBoost (Tuned) ===\n","Best Params: {'subsample': 1.0, 'n_estimators': 300, 'max_depth': 5, 'learning_rate': 0.01, 'colsample_bytree': 0.7}\n","Akurasi: 0.7840909090909091\n","                 precision    recall  f1-score   support\n","\n","         Normal       0.78      1.00      0.88       345\n"," Stunting Berat       0.00      0.00      0.00        23\n","Stunting Ringan       0.00      0.00      0.00        72\n","\n","       accuracy                           0.78       440\n","      macro avg       0.26      0.33      0.29       440\n","   weighted avg       0.61      0.78      0.69       440\n","\n"]},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.12/dist-packages/sklearn/metrics/_classification.py:1565: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n","  _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n","/usr/local/lib/python3.12/dist-packages/sklearn/metrics/_classification.py:1565: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n","  _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n","/usr/local/lib/python3.12/dist-packages/sklearn/metrics/_classification.py:1565: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n","  _warn_prf(average, modifier, f\"{metric.capitalize()} is\", len(result))\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 500x400 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["print(\"\\n==== 10. Perbandingan Akurasi Model ====\")\n","\n","try:\n","    models = ['RF Unoptimized', 'RF GridSearch', 'XGBoost Tuned']\n","    accuracies = [acc_rf_un, acc_rf_best, acc_xgb]\n","    accuracies_percent = [a * 100 for a in accuracies]\n","\n","    plt.figure(figsize=(8, 5))\n","    ax = sns.barplot(x=models, y=accuracies_percent, palette='viridis')\n","    plt.title(\"Perbandingan Akurasi Model\", fontsize=14)\n","    plt.ylabel(\"Akurasi (%)\", fontsize=12)\n","\n","    min_acc = min(accuracies_percent)\n","    max_acc = max(accuracies_percent)\n","    plt.ylim(max(0, min_acc - 10), min(100, max_acc + 5))\n","\n","    for i, v in enumerate(accuracies_percent):\n","        text_pos = v - (max_acc * 0.01)\n","        plt.text(i, text_pos, f\"{v:.2f}%\", ha='center', color='white', fontweight='bold', fontsize=12)\n","\n","    plt.show()\n","\n","    print(\"\\n=== Ringkasan Akurasi ===\")\n","    for m, acc in zip(models, accuracies_percent):\n","        print(f\"{m}: {acc:.2f}%\")\n","\n","    print(\"\\n💡 Interpretasi:\")\n","    print(f\"- Model dengan akurasi tertinggi adalah: {models[np.argmax(accuracies)]} ({max_acc:.2f}%)\")\n","    print(f\"- Model yang di-'tuning' (GridSearch/Tuned) seringkali memberikan akurasi yang lebih baik.\")\n","    print(\"\\nPENTING: Jangan hanya lihat akurasi!\")\n","    print(\"Karena data Anda tidak seimbang (banyak 'Normal'), akurasi tinggi bisa menipu.\")\n","    print(\"Lihat kembali 'Classification Report' & 'Confusion Matrix' dari Blok 7, 8, 9 untuk memeriksa:\")\n","    print(\"  1. Apakah model Anda bisa memprediksi 'Stunting Ringan' & 'Stunting Berat' (Recall > 0)?\")\n","    print(\"  2. Atau model Anda hanya 'menebak' semua anak sebagai 'Normal'?\")\n","\n","except NameError as e:\n","    print(\"\\n--- ERROR ---\")\n","    print(f\"Variabel tidak ditemukan: {e}\")\n","    print(\"Pastikan Anda telah menjalankan Blok 7, 8, dan 9 setidaknya satu kali sebelum menjalankan blok ini.\")\n","except Exception as e:\n","    print(f\"\\nTerjadi error tak terduga: {e}\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":875},"id":"pwLaDuwKT4Es","executionInfo":{"status":"ok","timestamp":1761566618204,"user_tz":-420,"elapsed":218,"user":{"displayName":"NICHOLAS DANIARDI","userId":"13862910458135710281"}},"outputId":"bd9f7290-864d-479a-c8fc-61dc8b077b4f"},"execution_count":77,"outputs":[{"output_type":"stream","name":"stdout","text":["\n","==== 10. Perbandingan Akurasi Model ====\n"]},{"output_type":"stream","name":"stderr","text":["/tmp/ipython-input-748276904.py:13: FutureWarning: \n","\n","Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n","\n","  ax = sns.barplot(x=models, y=accuracies_percent, palette='viridis')\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 800x500 with 1 Axes>"],"image/png":"iVBORw0KGgoAAAANSUhEUgAAAsYAAAHICAYAAABNiixYAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAAPYQAAD2EBqD+naQAAcH1JREFUeJzt3Xd8zdfjx/HXzV6SCLFXjISQSOwRo/ZWHfYqiipF+Zb6tkqrdKJWa/NVVbt2qVFVe+8de68sSSSS+/tDc3+umxARcun7+Xj00dzzOZ/zOZ/rnuR9P/d8zjUYjUYjIiIiIiL/cjYZ3QEREREREWugYCwiIiIigoKxiIiIiAigYCwiIiIiAigYi4iIiIgACsYiIiIiIoCCsYiIiIgIoGAsIiIiIgIoGIuIiIiIAArGIvICbd++HT8/P8aOHZvRXUmVgQMH4ufnx8WLF01lL9s5ZJSxY8fi5+fH9u3bM7or6WbRokX4+fmxaNGijO5KmtSoUYMaNWo8Uxuv4r+ryMMUjEX+ZS5evIifn5/ZfyVKlKBatWr069ePY8eOZXQXxYrt3LnT9LpZtWpVRnfHqiW9sfLz8+Pnn39OsV6fPn1M9V7W0C3yqrDL6A6ISMbIly8fTZo0ASA6Opp9+/axfPly1qxZw4wZMyhdunQG99A6BQYGsnLlSjJnzpzRXckQCxYsAMBgMLBw4ULq16+fwT16cWrXrk3JkiXJli3bU+1nZ2fHwoULadu2rcW2sLAw1q1bh52dHffv30+vropIGikYi/xL5cuXj169epmVjRo1ip9++onRo0cza9asDOqZdXN2dqZQoUIZ3Y0MERUVxerVq/Hz8yNr1qxs3ryZK1eukDNnzozu2guRKVMmMmXK9NT7ValShQ0bNnDs2DGKFi1qtm3p0qXExcVRo0YN1q9fn15dFZE00lQKETFp164dAAcPHjQrX7t2LR06dKBs2bIEBATQqFEjpk6dSkJCglm9h+dgrl+/npYtWxIcHJzsvMZdu3bRrl07goODKVOmDL169eLcuXMW9bZt28bHH39M3bp1CQ4OJjg4mDfeeIO5c+cmew5+fn60a9eOmzdvMmDAAMqXL09gYCDNmzdPcV7kyZMn6datG8HBwZQuXZp3332XEydOJFs3pTnGSfM37969y7BhwwgJCaFEiRI0btyY33//Pdm2Ll68SJ8+fShXrhzBwcG0bduWnTt3JjuPMy4ujlmzZtG5c2eqVatGiRIlqFixIj179uTIkSMWbT/8b/H333/TsmVLSpYsSfny5RkwYAB37txJtk+Ps3z5cmJiYnj99ddp2rQpiYmJT/3R/4kTJ6hatSply5Zl165dwP//myUnuXmxSVMULly4wLRp02jQoAElSpRg4MCBAFy7do0xY8bQvHlzKlasSIkSJahRowZDhgzh1q1bFseIjIzkhx9+oEGDBgQHB1OqVClq167NgAEDuHTpkqleWucYN2vWDFtbW9PV9octWrSIQoUKERwcnOL+u3fvpmvXrpQrV46AgADq1avHmDFjiImJSbb+2rVrefPNNwkMDKRSpUp88sknhIeHp9h+XFwc06dPp1mzZgQFBREcHEzr1q1Zt27dU52nyKtAwVhELBgMBtPP33//Pe+//z5nzpyhdu3atG7dGkdHR7755hv69u2b7P6///47vXr1IkuWLLRu3ZoqVaqYbd+3bx8dO3bEzc2Ndu3aUbZsWf744w9atmzJhQsXzOpOnjyZXbt2ERAQQJs2bWjcuDFhYWEMHjyYr776KtnjR0RE0Lp1a06ePEnTpk2pXbs2hw4donPnzhaB98SJE7Rs2ZK//vqLKlWq0KZNG+Lj42nVqpVFX54kPj6ezp07s3nzZurWrUuTJk24cOECffr04e+//zare+3aNVq2bMmqVasIDAykXbt2ZM6cmXfeeYf9+/dbtB0eHs7w4cOJi4ujWrVqdOzYkXLlyrFx40ZatmzJgQMHku3T+vXr6d69O9myZaN169bkzZuX3377jR49ejzVucGDaRS2trY0btyYOnXq4OLiwqJFizAajanaf9euXbRp0waA2bNnU6ZMmafuw8O++OILJk6cSIkSJejQoQO+vr6m40yfPp0sWbLQsGFD2rVrR968eZkzZw4tWrQgMjLS1IbRaKRz585MmDABDw8PmjdvTosWLShWrBjr169P9s3a08qePTuVK1dm2bJlxMXFmcoPHz7M0aNHeeONN1Lcd9WqVbRr144dO3ZQs2ZNOnTogLOzM+PHj6dDhw7cu3fPrP5vv/3G+++/z9mzZ2natCmvv/46e/bs4Z133jE7dpK4uDg6d+7MV199hdFo5K233qJJkyZcvnyZHj16PHZutMgrySgi/yoXLlww+vr6Gjt16mSx7YcffjD6+voa27VrZzQajca///7bVPfu3bumeomJicbBgwcbfX19jb///rupfOHChUZfX19j0aJFjZs3b7Zof9u2bUZfX1+jr6+vcc6cOWbb5syZY/T19TV269bNrPz8+fMW7cTHxxvfeecdY7FixYyXLl0y25bU/pAhQ4wJCQmm8nnz5hl9fX2Nn376qVn9tm3bGn19fY1LliwxK//+++9NbV24cMHiHMaMGWNW/7XXXjP6+voa33vvPeO9e/dM5Vu2bEn2+e7fv7/R19fX+OOPP5qVz58/33Tcbdu2mcrv3btnvHr1qsVzceLECWNQUJCxY8eOZuVJ/xb+/v7GXbt2mcrv379vOue9e/datJeSY8eOWZzHRx99ZPT19TVu2bLFov6YMWPMzmHt2rXGwMBAY926dZP9N2vbtm2yx33ttdeMr732mlnZgAEDjL6+vsaqVatatGU0Go03b940RkVFWZQvXrzY6Ovra5wwYYLFefXo0cOi/r1798zaSXpOFy5cmGxfH5XUz7179xp///13o6+vr3HlypWm7UOGDDH6+/sbb9y4YZw4caJF25GRkcbSpUsbS5QoYTx69KipPCEhwdinTx+jr6+vcdy4cWb1S5UqZQwKCjKGhoaayuPi4oxt2rQx+vr6WjyXI0eONPr6+hpHjx5tTExMNGvrjTfeMBYvXtzsdffov6vIq0ZXjEX+pc6fP8/YsWMZO3YsX3/9NW3atGH8+PE4OjqargQnXS364osvcHFxMe1rMBjo378/BoOBFStWWLRds2ZNKlWqlOKxCxQoQPPmzc3KmjdvToECBfjzzz+5ffu2qTxv3rwW+9vZ2dGyZUsSEhKSnR7h4uJC//79sbH5/19xzZo1w87OjkOHDpnKLl++zI4dO/Dz8zPdiJikW7duuLu7p3gOKfn4449xcHAwPa5YsSK5c+c2O25cXBy///47WbJkoVOnTmb7v/nmm/j4+Fi06+DgQPbs2S3KixQpQvny5dm5cyfx8fEW2xs1amR2I6WtrS3NmjUDLKfMPE7SNIDXX3/dVJb0c3JTBB42f/58evXqha+vL7/88gu5cuVK9XEfp3Pnzsm2lSVLFlxdXS3KmzZtipubG1u2bLHY5uTkZFHm4OCQbDtpUaNGDTJnzszChQsBuHfvHitWrKBatWpkzZo12X3Wrl1LZGQkb775ptncZBsbG/7zn/9gZ2fH4sWLzepHRUVZvIbs7e3p06ePRfuJiYnMmTOHfPny8cEHH5h9UuTm5sb7779PfHw8f/zxx7OevshLQzffifxLnT9/nnHjxgEP/nBmyZKFRo0a0bVrV/z8/ADYv38/Li4upj/mj3JyciI0NNSiPDAw8LHHLlWqlFlohQd/7EuVKsXZs2c5duyYKVhHRUUxbdo01q5dy4ULF4iOjjbb7/r16xbtFyhQwCLQ2NnZkSVLFiIiIkxlSUvTJbcCh6urK0WLFmXHjh2PPZeHubu7Jxvks2fPzr59+0yPQ0NDiYuLo0SJEmYhGh686QgODubMmTMW7Rw9epQpU6awe/dubt68aRGE79y5Y7FiQvHixS3ayZEjB4DZc/E4cXFxLF26FFdXV2rXrm0qL1++PDlz5uSPP/4gPDwcDw8Pi31nzJjB+vXrCQkJYezYsWZvsJ7V415na9asYe7cuRw+fJiIiAiz+fAPv2YKFSqEn58fy5cv5+rVq9SqVYty5cpRrFgxi9fos7C3t6dJkybMmjWLa9eusXPnTsLDw3nzzTdT3Ofo0aMAlCtXzmJbrly5yJMnD2fPniUqKgo3N7fHvp6Dg4OxszP/k3/mzBnCw8PJli2b6XfBw5LeoCY3xkVeVQrGIv9SISEhTJ069bF1wsPDuX//frJ/NJM8GlThwRW7x0npClnSfklzQOPi4mjfvj2HDx/G39+fJk2a4OnpiZ2dHZcuXWLx4sXJzpt0c3NLtn07OzsSExNNj5OOk1J/U+pnSlJaseDR40ZFRT31cffs2UOHDh0AqFy5MgUKFMDFxQWDwcDatWs5duxYqp8LW1tbALM+Pc7atWsJCwvjjTfeMLuyamNjQ+PGjZk0aRLLly83zR9+2O7du4EHKzOkZyiGlJ+/adOm8fXXX+Pl5UXlypXJkSOHqd8zZ840e0NhZ2fHzJkzGTduHKtXrzbNW/fy8qJNmza89957pufrWb355pvMnDmTRYsWsWPHDry9valWrVqK9ZNeJym9DrNly8bZs2e5e/cubm5uj30929ra4unpaVYWFhYGPLj59OTJkyn2I6Wb/EReRQrGIpKipFD1tN9y9fBHssm5efNmsuVJKwYkBcx169Zx+PBh3nrrLb788kuzuitWrDD7GDktko6T3EoFj+vns0p6Xp/muD/99BNxcXHJ3rT28NXo5yFpqsSiRYtSXJFhwYIFyQbjL7/8kh9//JERI0ZgY2ND+/btLeoYDIYU1/CNjIxM8Q1Hcq+z+/fvM2HCBLy9vVmyZIlZSDQajUyZMsVin8yZM/Ppp5/yySefEBoayrZt25g1axZjx47F3t6ebt26JXv8p+Xn50dAQACzZ8/m1q1bdOrUyeIq7sOSXicpvQ5v3LgBYPp05HGv54SEBMLCwsym4yS1X7duXcaMGZOGMxJ59WiOsYikKDAwkLCwMM6ePZuu7e7Zs8fiamViYiJ79uzBYDCY5lMmrQpRs2ZNizaSlvp6FknHSbqq+bC7d+8+t28BLFiwIA4ODhw+fNjiKq/RaEw26J4/fx5PT0+LUBwTE5Pscm3p5dKlS2zdupWsWbPy1ltvJftfnjx5OHLkSLL9cHd3Z8aMGZQoUYIvv/ySmTNnWtTx8PDg2rVrFuUXL15M9XSPJHfu3CEyMpLg4GCLK6cHDx4kNjY2xX0NBgOFChWiTZs2TJ8+HSDd1xZ+8803uXHjBomJiY+dRgFQrFgxgGSn81y5coULFy6QN29eU8B93Ot57969Fm8+ChUqhJubG4cOHUp2frrIv5GCsYikKGlt2UGDBiW77u2NGzc4ffr0U7d79uxZ5s2bZ1Y2b948zp49S/Xq1fHy8gIw3Vj16B/6HTt2MH/+/Kc+7qNy5cpF2bJlOX78OEuXLjXbNnHixKcOZanl4OBA3bp1uXnzJjNmzDDb9ttvvyU7pzN37tyEh4ebfeSdkJDA119/bXazYnpbtGgRiYmJtGjRgi+//DLZ/7p27QqkfBOeu7s706dPJyAggOHDh1ucc4kSJbh06ZJZAIyLi0txOb7HyZIlC05OThw+fNhsCkB4eDjDhg2zqH/x4kUuXrxoUZ50lfbROeDPqkmTJowfP57JkydTsGDBx9atVasWmTJlYtGiRWb/7kajke+++4779++bbqSEB28g3dzcWLhwodkc9fj4eH744QeL9u3s7GjVqhWXLl3i66+/TjYcnzhxIsVPNkReRZpKISIpqlq1Kj169GDChAnUqVOHKlWqkCtXLsLCwjh37hy7d++mT58+T/1NcCEhIQwbNoyNGzdSpEgRTp48yYYNG8icOTP//e9/TfVee+01cufOzZQpUzh58iRFihThzJkz/Pnnn9SqVYvVq1c/8zkOHjyYVq1aMWDAANauXUuBAgU4cOAABw8epEyZMulyZTo5/fr1Y+vWrXz//ffs3LkTf39/zpw5w4YNG6hSpQqbNm0yu/mrbdu2/P3337Ru3Zr69evj4ODAjh07uHbtGuXKlXuqmwRTK+kLPAwGg1kAe1SDBg0YPnw4y5YtY8CAATg6OlrUSQrHnTt3ZsSIEQB07NgRgHfeeYfNmzfTtWtXGjZsiLOzM5s3b8bd3R1vb++n6rONjQ2tW7dm2rRpNG3alNdee42oqCj++usvcufObXFz4rFjx+jZsyeBgYEUKlQIb29vrl27xtq1a7GxsTH1Mb24urpSq1atVNV1c3Pjiy++oF+/fjRv3pz69evj5eXFli1bOHz4MIGBgXTp0sVUP1OmTHzyyScMHDiQt956i4YNG+Lm5saff/6Jk5NTss/lBx98wJEjR5g1axYbN26kTJkyZMmShWvXrnHixAmOHTvG3Llzn3jfgMirQleMReSxevfuzfTp0yldujRbt25lxowZ/Pnnn8THx9OzZ08aN2781G0GBQUxY8YMoqKimDVrFjt27KBWrVrMnTvXbFUHV1dXZs6cSd26dTl48CCzZ8/m+vXrfPfdd8nOZ00LX19f5syZYwqjP//8M/b29syZMyfZFSbSS86cOfn111+pV68ee/fuZebMmdy6dYtp06aRP39+wPzGuddee40xY8aQN29eli5dyvLlyylYsCALFiwgd+7cz6WPW7Zs4fLly5QtW/axz0WmTJmoXbs2ERERrFmz5rH1pk2bRnBwMCNGjGDatGnAgzdKo0ePJm/evCxZsoTff/+dypUrM23atDRdsf3www/p27cvBoOBX375hS1btpi+rdHe3t6sbokSJXj33XcxGAxs3LiRadOmsWPHDipVqsScOXOSncbzItWvX5///e9/lClThj/++IMZM2Zw9+5devTowcyZMy3ehDRr1ozx48eTP39+Fi9ezG+//UapUqWYPn16ss+lg4MDkydP5vPPPydr1qysWbOGmTNnsmvXLry9vRkyZIjpi1NE/g0MRmMqv7JIREReiFatWrFv3z527dqVbuvoiojIk+mKsYhIBkluDeYlS5awZ88eKlWqpFAsIvKC6YqxiEgGKV++PMWKFaNw4cLY2Nhw9OhRduzYgaurK3PmzDF90YqIiLwYCsYiIhlk1KhRrF+/nitXrhATE0PmzJkpX748PXr0eOobGkVE5NkpGIuIiIiIoDnGIiIiIiKAgrGIiIiICKAv+Hhme/fuxWg0WqyNKSIiIiLWIT4+HoPBQHBw8GPrKRg/I6PRiKZpi4iIiFiv1GY1BeNnlHSlOCAgIIN7IiIiIiLJOXjwYKrqaY6xiIiIiAgKxiIiIiIigIKxiIiIiAigYCwiIiIiAigYi4iIiIgACsYiIiIiIoCCsYiIiIgIoGAsIiIiIgIoGIuIiIiIAArGIiIiIiKAFX4l9Lp16/jpp584deoUrq6ulC5dmv79+5M3b14AoqKimD59Ohs3buTs2bM4ODgQGBhI37598fPze2zb27dvp3379hblDRo0YNSoUc/lfERERETk5WBVwXj79u307NmT119/nb59+xIWFsYPP/xAp06dWLZsGU5OTly+fJm5c+fy5ptv0qdPH+7du8e0adNo0aIFCxcupFChQk88zogRIyhYsKDpcebMmZ/naYmIiIjIS8CqgvGKFSvIlSsXw4cPx2AwAODl5UWHDh04dOgQZcqUIU+ePPzxxx84Ozub9qtQoQI1atTgl19+4dNPP33icYoUKUJAQMBzOw8REREReflYVTC+f/8+rq6uplAMkClTJgCMRiMALi4uFvu5urqSL18+rl+//mI6KiIiIiKvHKsKxm+88QZLlixh9uzZNGnShLCwMEaOHIm/vz+lSpVKcb+IiAhOnjxJpUqVUnWcrl27EhYWhre3Nw0bNqR37944OTmlud9Go5Ho6Og07y8iIiIiz4/RaDS78JoSgzHpUqyV2LBhA/369ePu3bsAFCtWjClTppA1a9YU9/n0009Zvnw5q1atIkeOHCnWO3LkCCtWrKBs2bI4Ojqybds2pk2bRqVKlZg4cWKa+nvw4EHi4uLStK+IiIiIvBgODg5PnEprVVeM9+zZw0cffUTz5s2pXr06YWFhTJgwga5du/LLL78ke1V34cKFzJs3j6+++uqxoRjA398ff39/0+OKFSuSLVs2Pv/8cw4cOEBgYGCa+m1vb0/hwoXTtK+IiIiIPF+nTp1KVT2rCsbDhg2jQoUKDBw40FQWFBRE9erVWbJkCS1atDCrv3HjRgYPHkyPHj1o1qxZmo5Zv359Pv/8cw4dOpTmYGwwGJKd+ywiIiIiGS810yjAyr7g4/Tp0xQtWtSsLEeOHGTOnJnz58+ble/bt4/evXvz+uuv07t37xfZTRERERF5BVlVMM6VKxdHjhwxK7t06RJ37twhd+7cprJTp07RrVs3KlSowNChQ5/pmCtWrADQ8m0iIiIi/3JWNZWiZcuWDB8+nGHDhlGjRg3CwsL48ccfyZIlC/Xr1wfg1q1bdO7cGUdHR9P6xknc3NxMc30vXbpE7dq16dGjBz179gSgf//+5M+fH39/f9PNdzNmzKBWrVoKxiIiIiL/clYVjNu3b4+DgwNz5sxh4cKFuLq6EhQUxOjRo03fTnfq1CmuXr0KQMeOHc32L1euHLNmzQIeLMuRkJDAw4tuFClShGXLljFt2jTi4+PJnTs33bt3p2vXri/mBEVERETEalndcm0vm4MHDwKaiiEiIiJirVKb16xqjrGIiIiISEZRMBYRERERQcFYRERERARQMBYRERERARSMRUREREQABWMREREREUDBWEREREQEUDAWEREREQEUjEVEREREAAVjERERERFAwVhEREREBFAwFhEREREBFIxFRERERAAFYxERERERQMFYRERERARQMBYRERERARSMRUREREQABWMREREREUDBWEREREQEUDAWEREREQEUjEVEREREAAVjERERERFAwVhEREREBFAwFhEREREBFIxFRERERAAFYxERERERQMFYRERERARQMBYRERERARSMRUREREQABWMREREREUDBWEREREQEUDAWEREREQEUjEVEREREAAVjERERERHACoPxunXrePvttwkODiYkJITevXtz4cIFi3rz58+nbt26BAQE0KRJEzZs2JCq9q9du0avXr0IDg6mXLly/Pe//yUqKiq9T0NEREREXjJWFYy3b99Oz549KVy4MOPHj2fQoEEcO3aMTp06ERsba6q3YsUKPv30U+rXr8/kyZMJCgqiZ8+e7Nu377Htx8fH06VLF86ePcv333/PkCFD+Pvvv+nXr99zPjMRERERsXZ2Gd2Bh61YsYJcuXIxfPhwDAYDAF5eXnTo0IFDhw5RpkwZAMaMGUPDhg3p06cPABUqVODEiROMHz+eyZMnp9j+6tWrOXnyJCtXrqRgwYIAuLu707lzZw4cOEBgYODzPUERERERsVpWdcX4/v37uLq6mkIxQKZMmQAwGo0AXLhwgbNnz1K/fn2zfRs0aMDWrVuJi4tLsf2//voLPz8/UygGqFy5Mp6enmzcuDE9T0VEREREXjJWFYzfeOMNTp8+zezZs4mMjOTChQuMHDkSf39/SpUqBUBoaCgAPj4+ZvsWKlSI+Pj4ZOcjJwkNDTULxQAGgwEfHx9TuyIiIiLy72RVUynKlCnDuHHj6NevH59//jkAxYoVY8qUKdja2gIQHh4OPJgC8bCkx0nbkxMREWG6Av0wDw+Px+73JEajkejo6DTvLyIiIiLPj9FoNJuRkBKrCsZ79uzho48+onnz5lSvXp2wsDAmTJhA165d+eWXX3BycsroLiYrPj6eo0ePZnQ3RERERCQFDg4OT6xjVcF42LBhVKhQgYEDB5rKgoKCqF69OkuWLKFFixZ4eHgAEBkZibe3t6leREQEgGl7ctzd3ZNdmi08PJycOXOmud/29vYULlw4zfuLiIiIyPNz6tSpVNWzqmB8+vRpatasaVaWI0cOMmfOzPnz5wFMc4QfnS8cGhqKvb09efPmTbH9ggULcuLECbMyo9HImTNnqFy5cpr7bTAYcHFxSfP+IiIiIvL8pGYaBVjZzXe5cuXiyJEjZmWXLl3izp075M6dG4C8efNSoEABfv/9d7N6K1eupGLFio+9TF61alWOHTvG2bNnTWVbt24lLCyMatWqpd+JiIiIiMhLx6qCccuWLVm7di3Dhg1jy5YtrFy5ku7du5MlSxaz5dl69erF8uXLGTNmDNu3b+ezzz7jwIED9OjRw1Tn0qVL+Pv7M27cOFNZ3bp1KVKkCL169WLDhg2sXLmSQYMGUb16da1hLCIiIvIvZ1VTKdq3b4+DgwNz5sxh4cKFuLq6EhQUxOjRo8mcObOpXqNGjYiJiWHy5MlMmjQJHx8fxo0bR3BwsKmO0WgkISHBtP4xPJgLPGXKFIYNG8aHH36InZ0dtWvXZtCgQS/0PEVERETE+hiMDydHeWoHDx4EICAgIIN7IiIiIiLJSW1es6qpFCIiIiIiGUXBWEREREQEBWMREREREUDBWEREREQEUDAWEREREQEUjEVEREREAAVjERERERFAwVhEREREBFAwFhEREREBFIxFRERERAAFYxERERERQMFYRERERARQMBYRERERARSMRUREREQABWMREREREUDBWEREREQEUDAWEREREQEUjEVEREREAAVjERERERFAwVhEREREBFAwFhEREREBFIxFRERERAAFYxERERERQMFYRF4hCYmJGd0FETMvy2sy0fhy9FP+PTLqNWmXIUcVEXkObG1sGPTbQkJv3szorohQMGtWhr/+ZkZ3I1VsDDbMPPQ/rkZfy+iuiJDDJTsdSrTPkGMrGIvIKyX05k2OXb2S0d1Is5U9+5DL0/OxdbrMmsGuc2exMRhoXrosDQMC8cnqjZO9PZGxsRy/dpX5u3ey7tjRpz5+QO48zOjQCVubBx8o/n74EAMXLzBtt7OxpUtIFUrmyUuJXLnJ5OQEwK5zZ+kya4ZZWzYGA50qhdA0KJisrm6cu32LHzf+ycaTx83qda5chV6v1WTg4gX8fvjQU/dZ0sfV6GtcjLyY0d1IsyGVBpPFOctj6/yweyynwk5hwECVPCGUzVGG7K45cLCxJ+Z+DJeiLrHp4mb239j/1Mcv4J6fvmX6YGN4MHZ2X9vDjEMzTdttDbbUKVAbHw8fCnjkx9nOGYCTd04yZs84s7YMGKhdoBYVclbA3TET16NvsDJ0FYdumo+POvlr07hwI2Ycmsnua3ueus9iSVMpREReMvcTEgD4pEFjBtZrQEDuPLg5OmJnY0NmFxcq+BTk+7da8HapMk/Vrp2NLZ81bGIKxclxtrene9XqVCxYyBSKU9K6XAV6vlaTQ5cv0W32/7C3teX7t1tQLEdOU51smTLRuXIV9pw/p1Asz12C8cHYaVm0BW/7vUUBjwI42zlha2OLm4Mbfl5+dAnsREjuyk/Vrq3BllbFWplCcXIcbB1oULA+xbIUNYXilFTPW43GhRpxPuIc4/ZMwM5gS5eATuTNlMdUx8PRgzoFanM67LRCcTrSFWMRESvSf+E8HOzMfzX7ZMnKZ42aAHA9MpJDly+RydGJpiWDTHXGbVjHwcuXeD0omPrFAwBoXqYs8/fsSvWxO1cOoXC2bMTGx+Nkb59snUSjkQMXL7L/4gUSEhPpWCnlAFG7mD8AM7Zs5vi1qyzet5f+tetSs2gxjv5zVb93jdo42tnxzZrfU91PkeRMPTgdexvz121212y0LtYKgPB74ZyLOIeznTMVcpU31Vl2ejnnws9RMVcFSucoDUCVPCH8fWlzqo9dp0BtcrnlJC4hDgdbh2TrGI2JnAk/y5nwMyQaE6mVv2aK7QVnDwJg7bl1XIy6xNbL23jDtxklvUty4Z+r+k0LNcHe1p4FJxalup/yZArGIiJW5MiVyxZldf2Lm35etHc39xMTcXF0MF3ZvX33LlM2bwLgZmSkKRg/7srvowpm9aZz5SrExMcza9sWulaplmy9u3H3aD9jCgCVChZ+bDB2sH3wJybpCnf8/fsPyv8J/iXz5KVhQCAL9+x+qae/iHW4EHnBoqxU9mDTz5svbSHRmIijraPpym5kXBRrzv4BQHhchCkYP+7K76NyuGandoHaxCXEsf78Bur51E22XmzCPUbuGgVAMa+ijw3GdoZ/xs4/V7jvGx+MnaTg7+NRgLI5y7D50paXevqLNdJUChERK+Zkb0+jgJIAxCcksHDPbgCuRURw/vYtALxcXelSuQrlfQry7kOBduXBA6k6hgEDnzVsgoOdHT9u3MDFO3fSpe87zoYC0CAgEGd7B2r/E/C3nwnFgIGP6tQnMjaWcX+uS5fjiTzMwcaBcjnLApCQmMDmS1sACLsXxvXoGwBkcnCjToHa+GX2NQu0O6+m7pMWAwZaFW2FvY0dK0JXcjMmfW78PX7nBABlc5TBwdaB4GxB/5Qfx4CBt3zfJDo+muWnl6fL8eT/6YqxiIgVaxgQaJrLu+H4MW5ERZq29Z0/lxGvv4lv9uz0fO3/rz7diY5mwp/rUz2NokWZspTMm5fDly/z8/atpiD+rH76ayM5PTx5p1IInStXITY+nnEb1rH59CleDwqmeK5cfLvmd+5ERwOQxdWNW3ej0uXYImVzljHN5d1/4wARcRGmbVMOTKVD8fbkzpSLxoUamcqj4qJYEboy1dMoquQJoaCnD+cjzrPh/J+mIP6sVp35HS8nL2rlr0mdf65GLzu9nCO3jlIhZwXyuedj4YlFRMXfBSCTQyYi4yKf0KqkhoKxiIgVa176///Qzt21w2xbZGwMoTdv4Js9u1l5ZhcXavsXZ93xo9y+e/ex7edw96DXazWJT0hg6PIlJBqN6db3mPg4Plo0Hyd7e7xcXbkeEcH9xETcHB3pVb0mp2/c4NedO2hTrgI9qr2Gq6Mjd+/dY8LGDczesS3d+iH/TlVyh5h+3nRxk9m26PvRXI2+Su5MuczK3RzcCM4WxP4bB54YNDM7ZqZxoUYkJCbwy9E5GEm/sROXEMf0QzNwsHEgk4Mbd+6FkWhMxMnWicaFG3Hl7lX+uriJ6nmr0bBgA5zsnIi9H8uK0JX8eWFjuvXj30hTKURErFRQ3nz4Zc8BwKnr19l9/pxpm52NDZPbdqRe8RLcu3+fd3+eSYWvv+S7P1YDUK6AD182feOJx+hdoxaujo78b9sWTlx/PmvYxsbHczksjPv/fNlF1yrVyOLmxnd//E45Hx/+U6cet6Pv8sWKZdyOvst/6tSjYsFCz6Uv8u9Q0KMguTPlBuBy1BVOhZ02bbMx2PBBqZ6Uzl6K+IR4xu4ZR78N/2HRicUA+Hr50s6/7ROP0aRwY5zsnFh3fj2XoizvDUgPcYlx3Iq9bfqyi/o+9XB3yMSiE4vwzVyEN33fIDIuijlHfyUyLoo3fd+gqJffc+nLv4WuGIuIWKkWj7laXCZ/AfJnebBm686zZ9h59gwAP2/fyvvVXsPZwYGKBQvhZGdP7P34FI/hnSkT8GAt4c6Vq1hsr1e8BPWKl6DvvF/ZcOLYM59Tfq8stCpbng3Hj7E19DRDGjUFYNrmv1m8bw9GjAxu2IQ6/sXZGnr6Ca2JJK9KnpSvFhfJXIRsLtkAOHHnJCfunARgw4U/aVioAY62jhTLUhR7G3viE1MeOx6O7sCDFSnqFKhtsb109lKUzl6KyfuncODmwWc9JbK5ZKNq3iocuHGQY7ePm1bb+OPcH2y9/OATllbFWlIqeymO3T7+uKbkMXTFWETECmV2caVm0WIARMbGsvyRG+k8XVxMPzs7/P/yUA62dtjZ2ia7zRr8p049Eo1Gvl/74Mp2Vjc3AK6EhwFwOezB/7O6umVE9+QV4GbvRslsD+bJx9yPYcfVnY9sdzX97PjQ0mp2NnbYGmwf2ub4nHv6dN4s0gyj0cjikw+ubLs7PAjmt2Mf3Cx7K/b2P+WZMqaDrwirumLcrl07duzYkey2kSNHUrJkSWrWTH55EwcHBw4eTPkd2fbt22nf3vLrBRs0aMCoUaPS1mERkefkzeBSpmXNlh/cT0x8nNn20zdumH4unS8/XUKqcvjyJZoEBmH/TzC+HhHBnegHc4xzeXiyslcfwPxb6n7duYMNx82vBJfIlZv6JR4s+Xb0yhWWH9zPyRv/P82iVtEH6xP75chhKsvs4mIqD715g9CbN3hUlcK+hBQuwtTNm0wrXyQF4cwurmb/vxIe/sTnSCQ5lXJXxN7mwdjZcWUncQnmY+fK3aumnwtnLkzdAnU4F3GO8jnLY/fPfmGxYUTFP7gR1MvJi6GVPwPMv6Xur4ubOHDDPHfkd89PmX+WfLsQcYEdV3dy+e7/T7MI+iew53bLbSpzs3czlV+9e5Wrdy2nNBXPUhz/rP6sOfsHN2MerEZz+58g7GbvZvb/pKAsaWNVwfizzz4jKsr8juSZM2eyZs0aKlasiJubG3PnzjXbbjQa6dKlCxUqVEjVMUaMGEHBggVNjzNnzvzsHRcRSUc2BgNvlCptejxv106LOievX2P14UPULV4CgJ7Va1jUGbPhycugrT12xKKsSWCQKRifu33L4ka4795qbrFPIe9spvKf/vqTn/7602y7nY0t/WvX5XpkJFP+/v+Pthft28ObpUrTsmw5LoXdoWWZciQkJrJw7+4n9l3kUQYMVM5VyfR408W/LepcjrrMnmt7KJW9FACNCjW0qLMsFcug7btu+bXR5XOWMwXj6zE3LG6E6xzQyWKfnG45TeUrQ1ex6oz5l93YGmx5w/d1wu+Fs/rsGlP5lstbqZy7EtXyVuFWzC2q5qlCojGRLf8sSydpY1XBuHDhwhZl/fr1o3Llynh5eQEQFBRktn379u1ERUXRqFEji32TU6RIEQICAp65ryIiz0vVIr7k8vAEHqz5e+ZW8mujDvptEfsvXqB+iQB8snrjZG9PZGwshy9f4pcd29kSeuoF9vrx2pavQP4sWfhkyWKzq9/Hrl7hw/lz6VH9NSa2ac/5O7fpt2Aux69dfUxrIskrkbU4Xs4P8sLx2ye4Fp38DaUzD88iNPwsZbKXIrtrDhxs7Im5H8P5iPP8eWEjR28/+3z69FI9bzWyuWRj1uGfza5+X4y8yOQDU2lUsAE9S/XgZvRNphyYysWoSxnY25efwWhMx7V50tmePXto1aoV3333HY0bN062zqeffsrKlSvZsmULjo4pzwdKmkqxYMGCdA3GSdM3FLZFrEPLKRP1LWpiFYrmyMmvXbpldDdS7esd3+pb1MQq5MmUhwHl/pOubaY2r1nVFeNHLV++HBcXlxTnFcfHx7NmzRpq16792FD8sK5duxIWFoa3tzcNGzakd+/eOP2zeH5aGY1Gov9ZoF5EMobBYMDZ2TmjuyFiISYmBiu+BqWxI1YrPceO0WjEYDA8sZ7VBuP79++zatUqatSogctDd18/7K+//iIsLCxV0ygyZcpEly5dKFu2LI6Ojmzbto1p06YRGhrKxIkTn6mv8fHxHD169JnaEJFn4+zsjL+/f0Z3Q8TCmTNniImJyehupEhjR6xVeo8dh1Ss0mO1wXjz5s3cvn37saF32bJlZM2alYoVKz6xPX9/f7OBX7FiRbJly8bnn3/OgQMHCAwMTHNf7e3tk50fLSIvTmquBIhkBB8fH6u/YixijdJz7Jw6lbp7Lqw2GC9fvhxPT09CQkKS3X737l02bNjA22+/je1Da3Y+jfr16/P5559z6NChZwrGBoMhxavaIiLy76ZpCiJpk55jJ7VvAK3yCz5iY2NZu3Yt9erVw97ePtk6f/zxB7GxsSnelCciIiIi8jSsMhivX7+e6Ojox4be5cuXky9fPkqWLJnm46xYsQLQihIiIiIiYqVTKZYtW0auXLkoXbp0sttv377N1q1beffdd5PdfunSJWrXrk2PHj3o2bMnAP379yd//vz4+/ubbr6bMWMGtWrVUjAWEREREesLxuHh4WzatIkOHTqkOB9k1apV3L9/P8UrykajkYSEBLMJ20WKFGHZsmVMmzaN+Ph4cufOTffu3enatetzOQ8REREReblYXTD28PDg0KFDj63Tpk0b2rRpk+L2PHnycPz4cbOybt260a3by7PQuoiIiIi8WFY5x1hERERE5EVTMBYRERERQcFYRERERARQMBYRERERARSMRUREREQABWMREREREUDBWEREREQEUDAWEREREQEUjEVEREREAAVjERERERFAwVhEREREBFAwFhEREREBFIxFRERERAAFYxERERERQMFYRERERARQMBYRERERARSMRUREREQABWMREREREUDBWEREREQEUDAWEREREQEUjEVEREREAAVjERERERFAwVhEREREBFAwFhEREREBFIxFRERERAAFYxERERERQMFYRERERAQAu6fdISYmhs2bN7Nnzx5Onz7NnTt3MBgMZM6cmYIFC1KqVCkqVaqEi4vL8+iviIiIiMhzkepgfPz4caZPn86aNWuIjo7GycmJHDly4OHhgdFo5MyZM2zdupVp06bh7OxM3bp1eeedd/Dz83ue/RcRERERSRepCsZ9+vRhzZo1lChRgl69elGpUiUKFy6Mra2tWb2EhAROnTrF5s2bWb16Nc2aNaNevXqMHDnyuXReRERERCS9pCoY29jYsHDhQooVK/bYera2tvj5+eHn50enTp04evQokydPTpeOioiIiIg8T6kKxmm94lusWDFdLRYRERGRl4JWpRARERERIQ2rUiRn8eLFLFu2jGvXrpE1a1YaNGhA8+bNMRgM6dG8iIiIiMhz98zBePz48cyZM4cWLVqQLVs2Tp06xfDhwzl37hwfffTRU7XVrl07duzYkey2kSNH0rBhwxTrrFy5kkKFCj22/WvXrjFs2DD+/vtv7O3tqV27Nh9//DFubm5P1U8RERERefWkOhhfunSJ3LlzW5QvXryYkSNHUq5cOVOZt7c306dPf+pg/NlnnxEVFWVWNnPmTNasWUPFihVNZaVKlWLAgAFm9fLkyfPYtuPj4+nSpQsA33//PbGxsXz99df069ePiRMnPlU/RUREROTVk+pg3LBhQzp27Ei3bt1wdnY2lbu6unL58mWzupcvX8bV1fWpO1O4cGGLsn79+lG5cmW8vLxMZe7u7gQFBT1V26tXr+bkyZOsXLmSggULmtrp3LkzBw4cIDAw8Kn7KyIiIiKvjlTffDdr1iy2bdtGvXr1WLp0qan8/fff55NPPqF9+/b079+fN954g7lz59KzZ89n7tyePXu4ePEijRs3fua2/vrrL/z8/EyhGKBy5cp4enqycePGZ25fRERERF5uqQ7GAQEB/Prrr3z44Yd8//33tGjRggMHDlCnTh2WLl1KhQoVcHNzo0aNGixZsoTXX3/9mTu3fPlyXFxcqFmzpln5jh07CAoKIiAggLZt27Jz584nthUaGmoWigEMBgM+Pj6EhoY+c19FRERE5OX21DffNW3alDp16vDTTz/Rvn176tWrR79+/ejRo0e6duz+/fusWrWKGjVq4OLiYiovW7YsTZs2pUCBAly/fp2pU6fyzjvvMGvWLIKDg1NsLyIigkyZMlmUe3h4EB4e/kx9NRqNREdHP1MbIvJsDAaD2TQvEWsRExOD0WjM6G6kSGNHrFV6jh2j0Ziq1dLStCqFs7Mzffv25a233uLrr7+mbt26dOvWjXfeeQcHB4e0NGlh8+bN3L59m0aNGpmVf/DBB2aPq1evTqNGjZgwYUKGfctefHw8R48ezZBji8gDzs7O+Pv7Z3Q3RCycOXOGmJiYjO5GijR2xFql99hJTUZ9qmC8b98+NmzYQExMDCVLlqRhw4aMGzeOrVu3Mnz4cObNm8eAAQOoU6dOmjudZPny5Xh6ehISEvLYei4uLlSrVo3Vq1c/tp67u7vFihcA4eHh5MyZ85n6am9vn+yNgyLy4mjddLFWPj4+Vn/FWMQapefYOXXqVKrqpToYL1iwgMGDB1O6dGk8PT2ZN28ef/zxB6NHj6ZixYosWbKEX375hU8//ZSff/6Z//73v/j5+aWp87Gxsaxdu5YmTZpgb2+fpjYeVbBgQU6cOGFWZjQaOXPmDJUrV36mtg0Gg9l0DxERkSSapiCSNuk5dlL7BjDVN9/99NNPtGnThlmzZjF27FjGjh3L6tWruXDhwoOGbGxo27Yta9asoVChQrz99ttp6zmwfv16oqOjU7UaRXR0NH/++ScBAQGPrVe1alWOHTvG2bNnTWVbt24lLCyMatWqpbmvIiIiIvJqSHUwjoiIoECBAqbH+fLlw2g0EhERYVbPw8ODzz77jAULFqS5U8uWLSNXrlyULl3arHzXrl10796dhQsXsm3bNpYuXUqbNm24ceMG77//vqnepUuX8Pf3Z9y4caayunXrUqRIEXr16sWGDRtYuXIlgwYNonr16lrDWERERERSP5WiSpUqTJo0iUyZMuHu7s60adPImTMnRYoUSba+r69vmjoUHh7Opk2b6NChg8Vlb29vb+Lj4xk1ahRhYWE4OzsTHBzM0KFDzcKt0WgkISHBbF6Kvb09U6ZMYdiwYXz44YfY2dlRu3ZtBg0alKZ+ioiIiMirJdXBeMiQIXz11Vd88803xMbGEhAQwMSJE9NtFYokHh4eHDp0KNlt+fPnZ+rUqU9sI0+ePBw/ftyiPHv27IwdO/aZ+ygiIiIir55UB+NMmTLx5ZdfPs++iIiIiIhkmFTPMRYREREReZWlKhgPHjzYtPrE0zh//jyDBw9+6v1ERERERF60VE2luHLlCvXr16dChQo0aNCAihUrpvilGBcvXmTr1q2sWrWK7du3P/MawSIiIiIiL0KqgvHkyZPZvXs306ZNY/DgwSQkJODp6Unu3Lnx8PDAaDQSHh7OxYsXiYiIwNbWlqpVqzJz5kzKlCnzvM9BREREROSZpfrmu9KlS1O6dGlu377Nhg0b2LdvH6GhoVy9ehUAT09P6tSpQ1BQENWrVydLlizPrdMiIiIiIukt1cE4iZeXF2+++SZvvvnm8+iPiIiIiEiG0KoUIiIiIiIoGIuIiIiIAArGIiIiIiKAgrGIiIiICKBgLCIiIiICKBiLiIiIiAAKxiIiIiIiQCrXMS5atCg2Njbs27cPBwcHihYtisFgeOw+BoOBI0eOpEsnRURERESet1QF4/fffx+DwYCdnZ3ZYxERERGRV0WqgnGvXr0e+1hERERE5GWnOcYiIiIiIqQxGG/dupUpU6aYlS1YsIDq1atTqVIlhg8fTkJCQrp0UERERETkRUhTMB47dizHjh0zPT5+/DifffYZXl5elCtXjlmzZjF16tR066SIiIiIyPOWpmB8+vRpSpQoYXq8ZMkS3NzcmD17NqNHj+btt99myZIl6dZJEREREZHnLU3BOCYmBjc3N9PjTZs2ERISgrOzMwABAQFcvnw5fXooIiIiIvICpCkY58yZk4MHDwJw7tw5Tp48SUhIiGl7eHg4Dg4O6dNDEREREZEXIFXLtT2qcePGjB8/nmvXrnHq1Ck8PDyoWbOmafvhw4cpUKBAevVRREREROS5S1Mw7t69O/Hx8WzcuJGcOXPy1Vdf4e7uDkBYWBg7duygffv26dpREREREZHnKU3B2M7Ojr59+9K3b1+LbZ6enmzevPmZOyYiIiIi8iLpCz5EREREREjjFWOAe/fusXr1ao4cOUJkZCSJiYlm2w0GA8OHD3/mDv4bJSQmYmuj9yxiXfS6FBGRV12agvGlS5do3749ly5dwt3dncjISDw8PIiMjCQhIYHMmTPj4uKS3n3917C1seGrsYs4f+lmRndFBIB8ubMysNcbGd0NERGR5ypNwfibb74hKiqKefPmkSdPHipVqsSoUaMoXbo0//vf/5g9e7a++e4Znb90k1NnrmZ0N0RERET+NdIUjLdt20arVq0IDAwkLCzMVO7g4ECXLl04ffo0w4cPZ9KkSenVT3nJ/G/sB+TI5vnYOv2HzuTAkXPUqxFM1Qr+5M+dFXd3FwwYuB0WyYEj55i7ZDMXLt9K1TEDiuWndtVA/P3ykCdnVmxsDGbHeVTe3Flp3SyEgGL5yezpRmJiItdvhrNr32nm/PY3YeF3AbAxGGjxemXqVg/Cy9ONi1du8b/5G9m2+4RZey1fD6FTqxoM/2Ehf245nKo+i4iIiPVI04TB2NhYcufODYCbmxsGg4HIyEjT9uDgYHbv3p0+PZRX1v2EB/PSq1cqTpmShfDO6oGjgz0ODnbkyJaZOtWDGDu8C7lzeqWqvcrl/KhXI5h8ub1NoTgleXNlYeyXnalZJZBsWT2wt7PF0cGevLmy0qxBeUZ//g5OjvYANGtQnnda1uD46csMGPYzdna2fNavOUV8cpray5I5E62ahXDw6HmFYhERkZdUmq4Y58yZk2vXrj1owM6O7Nmzs2/fPurUqQPAqVOncHR0TL9eykvni1HzcbA3f3nlzZ2VD7s1BuDW7UiOn7oEQOi5axw8co6zF29wN/oeBfJ406FFdVxdnHBxdqRu9SCmzVn/xGOGhd/lr21HOHriIg1qlSJvrqwp1m1QszQuzg9eo6fPXmXG3A24uTjR4516ZHJzJlcOL8qULMTfO45RpYI/APOWbuH02aus3rCPbu3rULlcUU6euQJAlzY1cXCw48eZvz/9kyUiIiJWIU3BuEKFCqxbt46ePXsC0KxZMyZNmkRERASJiYksXbqUpk2bpmtH5eVyMvSKRVm1SsVNP69ct4eEf64YT5r1h1m9fYfOkCO7J280qACAs1Pqvl7819/+f/3sqhX9H1vX1eX/37itXLeH7XtOAlCxrB9V/wnCtrYPPlCxt7cF4P79BADi4u8D4ODwYPj4++ahZpVAVq7drXnhIiIiL7E0BeOuXbty8OBB4uLicHBwoHv37ly/fp3Vq1djY2NDo0aN+Pjjj9O7r/ISc3K0p3bVQOBBwFyxLvmpNvZ2thTIm41yQUVMZfsPn033/uw/cpZ6NYIBaFCzFNduhJPJ1YngEj4A3AmLYveBUAD2HTxDEZ+c1KwSwC+LNpmC896DZzAYoEfHekTdjWX6rxvSvZ8iIiLy4qQpGOfKlYtcuXKZHjs6OvLll1/y5ZdfPlNn2rVrx44dO5LdNnLkSKpVq8b06dPZuHEjZ8+excHBgcDAQPr27Yufn99j296+fXuyX1PdoEEDRo0a9Uz9lierWSUAVxcnADbvPMbtO1Fm2/PmysLUUe+blUVGxTBv6Rb+3nEs3fuzbtNB8uX25s2GFShUIAfDBrYybdu2+wQ/zlxN1N1YAGYt2Eg2bw+aN6lMy9dDuBcXz/Rf17Nz3ynqvRaEb6Fc/DhzNeGR0QBk9nDlzj837omIiMjL46mDcUxMDNWrV+fdd9+lS5cu6dqZzz77jKgo88A0c+ZM1qxZQ8WKFbl8+TJz587lzTffpE+fPty7d49p06bRokULFi5cSKFChZ54jBEjRlCwYEHT48yZM6frOUjyGtUpY/p56epdqdonITERw+PvoXsml67e4k54FNm9Pc3Ki/vlJah4Aa5cuwNA7L14vhy9ECfHpXi6u3LjdgQJCYm4ODvyTssanLt4gyW/76BZg/J0aF4dF2dHomPuMXPenyxeuf35nYCIiIikq6cOxs7Oztja2uLs7JzunSlcuLBFWb9+/ahcuTJeXl44OTnxxx9/mB27QoUK1KhRg19++YVPP/30iccoUqQIAQEB6dpvebzifnkplD8HAGcvXOfgUcul067dCKfv4Ok4OdpTsEAOWjStjKe7K51a1SQ6Jo6lq3ema59qVytJ//cezIP/a9sRfpi0HDc3Zz7/qCX583jTt1tjzl28wZETF037xN6L5+qNMNPjtm9VJbOnG9+M/43gEj6816Eul6/eZtKsP2jepBLvdajL+Ys3TFMyRERExLqlabm2OnXqsHr1aoxGY3r3x8yePXu4ePEijRs/WMnAxcXFIpC7urqSL18+rl+//lz7ImnX2OxqcfIBNy7+PoePX2D3gVDmL93CpFlrTNteq1wi3fvUoGYp08/zl24h8m4sV67dYc3G/abySmWLprh/npxZaFqvHFt2Hmf3gVDTjYW/LtnMynV7mLvkwY2A1SoWT7ENERERsS5pmmPcsGFDhg4dSvv27Xn77bfJnTs3Tk5OFvWKF3+2ULB8+XJcXFyoWbNminUiIiI4efIklSpVSlWbXbt2JSwsDG9vbxo2bEjv3r2T7fvTMBqNREdHP1MbSQwGw3O5Gp9RPN1dCClfDIC70bGs/euA2XZ7O1vi/1nt4WEPv+dyc322f5/kuGf6/+f44VUvXB762dnJPsX93+tQF2OikYn/BHgvTzcArt8IBx5cAQfI/E/5qyImJua5vyFOq1dt7Mirw5rHDWjsiPVKz7FjNBoxpGJ+ZpqCcbt27Uw/79plOV806eBHjx5NS/MA3L9/n1WrVlGjRg1cXFxSrPftt99iMBho1apVinUAMmXKRJcuXShbtiyOjo5s27aNadOmERoaysSJE9PcT4D4+PhnOteHOTs74+//+KXGXib1a5YyrWf8x18HiL0Xb7a9mG8e+nZrzLpNBzh7/jrRMXH45MtGq2Yhpjqnzpgv/bZm7mAArl4Po32vMabyfLmzkj+PNwCZXP//l3ygf348Mj14DW3a/uDf6dzFG6Z1jru2q83/5m3Ezc3J7Or26bPXkj2n8qWKUDa4ML/+9rdpHvK1f6ZYeLi7mP3/+s2wxz4/L5szZ84QExOT0d1I1qs2duTVYc3jBjR2xHql99hxcHjy8q9pCsYjRoxIy25PZfPmzdy+fZtGjRqlWGfhwoXMmzePr776ihw5cjy2PX9/f7OBX7FiRbJly8bnn3/OgQMHCAwMTHNf7e3tk50fnRapeTfzsrAxGMymLCxbk/xNd7lzeNH+7erJbrt1J5KZ8/5M1fGqVSxOu7erWZQ/3HadFp8DMGfR35QJLISTkwOFfXLy+YCWZvucvXDd4uo2gJ2tDd3a1eHW7Uh+WbTJVL5q/V4a1CpN03rluHo9jCZ1y5KQmMjKdXtT1feXhY+Pj9Ve+XqVxo68Wqx53IDGjliv9Bw7p06dSlW9NAXjZs2apWW3p7J8+XI8PT0JCQlJdvvGjRsZPHgwPXr0SHN/6tevz+eff86hQ4eeKRgbDIbHXtX+typfuohpxYe9B89w4dJNizoXr9xi8crtlCiaF++sHmRydSb2XjyXr91m177TLFqxzbQMWno6eeYKH3wylRZNKxNQLD+ZPd1ITEzk2o0wtu46wa+//W36Io+HNWtYgTy5svDN+N/Mrn6fOnOVod/No0OL6nz9SVsuXbvN59/P4/TZV+sLP/Rxq8jT07gRSZv0HDupfQOYpmD8vMXGxrJ27VqaNGmCvb3lPM99+/bRu3dvXn/9dXr37p0BPZTU2LrrhOkKbUpu34nix5mrn6rdlNqctWAjsxZsTHU7Zy/c4Otxvz3Vsecv3cL8pVuS3bZt9wm27T7xVO2JiIiI9UhTME7Nt9oZDAaGDx+eluZZv3490dHRptUoHnbq1Cm6detGhQoVGDp0aJraT7JixQoALd8mIiIiImkLxtu3W35pQWJiIjdu3CAhIQEvL69nuvy9bNkycuXKRenSpc3Kb926RefOnXF0dKRDhw4cOnTItM3Nzc00z/fSpUvUrl2bHj160LNnTwD69+9P/vz58ff3N918N2PGDGrVqqVgLCIiIiJpC8br169Ptjw+Pp65c+cyc+ZMpk2blqYOhYeHs2nTJjp06GAxH+TUqVNcvfpgzmbHjh3NtpUrV45Zs2YBD1bFSEhIMJuwXaRIEZYtW8a0adOIj48nd+7cdO/ena5du6apnyIiIiLyaknXOcb29va0bduWU6dO8cUXXzBp0qSnbsPDw8PsSvDDypcvz/Hjx5/YRp48eSzqdevWjW7duj11f0RERETk3yFN33z3JEWLFmXnzvT9Cl8RERERkefpuQTjLVu2aHkaEREREXmppGkqxbhx45Itj4yMZOfOnRw5ckRzd0VERETkpZKuwdjDw4O8efMydOhQmjdv/kwdExERERF5kdIUjI8dO5be/RARERERyVBpmmO8du3aJ9b59ttv09K0iIiIiEiGSFMw7tOnD3/99VeK2wcPHpzmdYxFRERERDJCmoJxs2bN6NWrF1u3bjUrT0xMpF+/fsyfP5/BgwenSwdFRERERF6ENAXjL774gnr16tGjRw927doFQFxcHO+//z6rV6/m66+/plWrVunaURERERGR5ynN33w3YsQI4uLi6Nq1K2PGjGHKlCns2bOH0aNHU6tWrfTso4iIiIjIc5fmL/iwsbHhu+++o2LFirz77rscOHCAiRMnKhSLiIiIyEspVVeMp0+fnuK2kiVLsnXrVqpUqcKxY8dMS7kZDAY6duyYLp0UEREREXneUhWMv/766yfWWb16NatXrzY9VjAWERERkZdJqoLxunXrnnc/REREREQyVKqCce7cuZ+64fDw8KfeR0REREQko6T55rvkxMXFsWrVKnr06EFISEh6Ni0iIiIi8lylebm2JEajka1bt7Js2TL++OMPoqKi8PLyolGjRunRPxERERGRFyLNwfjQoUMsW7aMFStWcPPmTQwGAw0aNKBt27YEBQVhMBjSs58iIiIiIs/VUwXjCxcusHTpUpYtW8a5c+fInj07jRs3JjAwkL59+1K3bl2Cg4OfV19FRERERJ6bVAfjFi1acODAATJnzkzdunUZNmwYZcqUAeD8+fPPrYMiIiIiIi9CqoPx/v37yZMnDwMHDqR69erY2T3z9GQREREREauR6lUpPv30U7y9venZsyeVK1dm8ODBbNu2DaPR+Dz7JyIiIiLyQqT6sm+bNm1o06YNFy5cYNmyZSxfvpx58+aRNWtWypcvj8Fg0A13IiIiIvLSeup1jPPmzUuPHj1YuXIlCxYsoGHDhuzYsQOj0cjQoUP59NNP2bBhA/fu3Xse/RUREREReS6eaaJwiRIlKFGiBAMGDGDbtm0sXbqUlStXMn/+fJydndm7d2969VNERERE5LlKlzvobGxsqFSpEpUqVWLo0KGsW7eOZcuWpUfTIiIiIiIvRLovLeHo6EiDBg1o0KBBejctIiIiIvLcPPUcYxERERGRV5GCsYiIiIgICsYiIiIiIoCCsYiIiIgIoGAsIiIiIgIoGIuIiIiIAArGIiIiIiKAgrGIiIiICGBlwbhdu3b4+fkl+9+KFStM9ebPn0/dunUJCAigSZMmbNiwIVXtX7t2jV69ehEcHEy5cuX473//S1RU1PM6HRERERF5iaT7N989i88++8wiqM6cOZM1a9ZQsWJFAFasWMGnn35K9+7dqVChAitXrqRnz57Mnj2boKCgFNuOj4+nS5cuAHz//ffExsby9ddf069fPyZOnPjczklEREREXg5WFYwLFy5sUdavXz8qV66Ml5cXAGPGjKFhw4b06dMHgAoVKnDixAnGjx/P5MmTU2x79erVnDx5kpUrV1KwYEEA3N3d6dy5MwcOHCAwMDD9T0hEREREXhpWNZXiUXv27OHixYs0btwYgAsXLnD27Fnq169vVq9BgwZs3bqVuLi4FNv666+/8PPzM4VigMqVK+Pp6cnGjRufzwmIiIiIyEvDqq4YP2r58uW4uLhQs2ZNAEJDQwHw8fExq1eoUCHi4+O5cOEChQoVSrat0NBQs1AMYDAY8PHxMbWbVkajkejo6Gdq4+E+OTs7p0tbIuktJiYGo9GY0d1IlsaOWCtrHjegsSPWKz3HjtFoxGAwPLGe1Qbj+/fvs2rVKmrUqIGLiwsA4eHhwIMpEA9Lepy0PTkRERFkypTJotzDw+Ox+6VGfHw8R48efaY2kjg7O+Pv758ubYmktzNnzhATE5PR3UiWxo5YK2seN6CxI9YrvceOg4PDE+tYbTDevHkzt2/fplGjRhndlSeyt7dPdn50WqTm3YxIRvHx8bHaK18aO2KtrHncgMaOWK/0HDunTp1KVT2rDcbLly/H09OTkJAQU5mHhwcAkZGReHt7m8ojIiLMtifH3d092aXZwsPDyZkz5zP11WAwmK5qi7zK9HGryNPTuBFJm/QcO6l9A2iVN9/Fxsaydu1a6tWrh729vak8aY7wo3OCQ0NDsbe3J2/evCm2WbBgQYv9jEYjZ86csZh7LCIiIiL/PlYZjNevX090dLRpNYokefPmpUCBAvz+++9m5StXrqRixYqPnTtStWpVjh07xtmzZ01lW7duJSwsjGrVqqVr/0VERETk5WOVwXjZsmXkypWL0qVLW2zr1asXy5cvZ8yYMWzfvp3PPvuMAwcO0KNHD1OdS5cu4e/vz7hx40xldevWpUiRIvTq1YsNGzawcuVKBg0aRPXq1bWGsYiIiIhY3xzj8PBwNm3aRIcOHZKdD9KoUSNiYmKYPHkykyZNwsfHh3HjxhEcHGyqYzQaSUhIMJuwbW9vz5QpUxg2bBgffvghdnZ21K5dm0GDBr2Q8xIRERER62Z1wdjDw4NDhw49ts7bb7/N22+/neL2PHnycPz4cYvy7NmzM3bs2Gfuo4iIiIi8eqxyKoWIiIiIyIumYCwiIiIigoKxiIiIiAigYCwiIiIiAigYi4iIiIgACsYiIiIiIoCCsYiIiIgIoGAsIiIiIgIoGIuIiIiIAArGIiIiIiKAgrGIiIiICKBgLCIiIiICKBiLiIiIiAAKxiIiIiIigIKxiIiIiAigYCwiIiIiAigYi4iIiIgACsYiIiIiIoCCsYiIiIgIoGAsIiIiIgIoGIuIiIiIAArGIiIiIiKAgrGIiIiICKBgLCIiIiICKBiLiIiIiAAKxiIiIiIigIKxiIiIiAigYCwiIiIiAigYi4iIiIgACsYiIiIiIoCCsYiIiIgIoGAsIiIiIgIoGIuIiIiIAArGIiIiIiIA2GV0B5KzePFiZs6cyenTp3FxcSEgIIBx48bh5OSEn59fivtt2rSJbNmyJbvt4sWL1KxZ06K8ZMmSzJs3L936LiIiIiIvJ6sLxj/++COTJ0+me/fuBAUFcefOHbZu3UpCQgIAc+fOtdhnwIABODs7pxiKH/bhhx9Svnx502NXV9f067yIiIiIvLSsKhiHhoYybtw4JkyYQLVq1UzldevWNf0cFBRkts/Fixc5e/Ys//nPf1J1jPz581u0ISIiIiJiVXOMFy1aRJ48ecxC8ZMsX74cg8FAo0aNnmPPRERERORVZ1XBeP/+/fj6+jJhwgQqVqxIiRIlaNmyJfv3709xnxUrVlC2bFly5MiRqmMMGTKEYsWKUbFiRT755BPCwsLSqfciIiIi8jKzqqkUN27c4NChQ5w4cYLPPvsMZ2dnfvrpJzp16sSaNWvIkiWLWf1jx45x4sQJPv/88ye27eDgQKtWrQgJCcHd3Z39+/fz008/cejQIebPn4+9vX2a+200GomOjk7z/g8zGAw4OzunS1si6S0mJgaj0ZjR3UiWxo5YK2seN6CxI9YrPceO0WjEYDA8sZ5VBeOkgPnDDz9QtGhR4MGqETVq1ODnn3+md+/eZvWXLVuGvb292RzklGTLlo0hQ4aYHpcrV44iRYrQrVs3/vjjDxo0aJDmfsfHx3P06NE07/8wZ2dn/P3906UtkfR25swZYmJiMrobydLYEWtlzeMGNHbEeqX32HFwcHhiHasKxu7u7nh6eppCMYCnpyf+/v6cOnXKrK7RaGTlypVUqVIFT0/PNB2vWrVquLi4cPjw4WcKxvb29hQuXDjN+z8sNe9mRDKKj4+P1V750tgRa2XN4wY0dsR6pefYeTRHpsSqgnHhwoU5f/58stvu3btn9nj37t1cvnw51atRPE8GgwEXF5eM7obIc6ePW0WensaNSNqk59hJ7RtAq7r57rXXXiMsLMxsWsKdO3c4fPgwxYsXN6u7bNkyXFxcqFGjRpqPt2HDBqKjowkICEhzGyIiIiLyarCqK8a1atUiICCADz74gL59++Lo6MikSZNwcHCgdevWpnr3799n9erV1KpVCycnp2Tb8vf35/XXX2f48OEAfPXVVxgMBoKCgnB3d+fAgQNMnDiREiVKUKtWrRdyfiIiIiJivawqGNvY2DBp0iRGjBjB4MGDiY+Pp0yZMsyePRtvb29Tvb///ps7d+48du3ihIQEEhMTTY8LFSrEnDlzmDdvHrGxsWTPnp233nqLDz74ADs7q3oaRERERCQDWF0i9PLy4ttvv31snerVq3P8+PHH1nl0+9tvv83bb7/9zP0TERERkVeTVc0xFhERERHJKArGIiIiIiIoGIuIiIiIAArGIiIiIiKAgrGIiIiICKBgLCIiIiICKBiLiIiIiAAKxiIiIiIigIKxiIiIiAigYCwiIiIiAigYi4iIiIgACsYiIiIiIoCCsYiIiIgIoGAsIiIiIgIoGIuIiIiIAArGIiIiIiKAgrGIiIiICKBgLCIiIiICKBiLiIiIiAAKxiIiIiIigIKxiIiIiAigYCwiIiIiAigYi4iIiIgACsYiIiIiIoCCsYiIiIgIoGAsIiIiIgIoGIuIiIiIAArGIiIiIiKAgrGIiIiICKBgLCIiIiICKBiLiIiIiAAKxiIiIiIigIKxiIiIiAigYCwiIiIiAigYi4iIiIgAVhqMFy9ezOuvv05AQADly5enS5cuxMbGAjBw4ED8/Pws/vvrr7+e2G5kZCSDBg2iXLlyBAcH88EHH3D9+vXnfToiIiIi8hKwy+gOPOrHH39k8uTJdO/enaCgIO7cucPWrVtJSEgw1cmbNy/fffed2X6FChV6Ytt9+vTh1KlTDBkyBEdHR0aPHs27777LwoULsbOzuqdCRERERF4gq0qDoaGhjBs3jgkTJlCtWjVTed26dc3qOTk5ERQU9FRt7927l7///pupU6cSEhICgI+PDw0aNGDNmjU0aNDgmfsvIiIiIi8vq5pKsWjRIvLkyWMWitPLX3/9hbu7O5UrVzaVFSxYkGLFiqVqGoaIiIiIvNqs6orx/v378fX1ZcKECcyaNYvIyEhKlCjBxx9/TMmSJU31zp07R+nSpbl37x6+vr706NGDWrVqPbbt0NBQfHx8MBgMZuUFCxYkNDT0mfptNBqJjo5+pjaSGAwGnJ2d06UtkfQWExOD0WjM6G4kS2NHrJU1jxvQ2BHrlZ5jx2g0WmTA5FhVML5x4waHDh3ixIkTfPbZZzg7O/PTTz/RqVMn1qxZQ5YsWShWrBgBAQEULlyYyMhI5syZw/vvv88PP/xAvXr1Umw7IiKCTJkyWZR7eHhw6NChZ+p3fHw8R48efaY2kjg7O+Pv758ubYmktzNnzhATE5PR3UiWxo5YK2seN6CxI9YrvceOg4PDE+tYVTBOuvL6ww8/ULRoUQBKlixJjRo1+Pnnn+nduzcdOnQw26dGjRq0bNmSMWPGPDYYP0/29vYULlw4XdpKzbsZkYzi4+NjtVe+NHbEWlnzuAGNHbFe6Tl2Tp06lap6VhWM3d3d8fT0NIViAE9PT/z9/VM8IRsbG+rUqcO3335LbGwsTk5OKbZ99epVi/Lw8HA8PDyeqd8GgwEXF5dnakPkZaCPW0WensaNSNqk59hJ7RtAq7r57nFXXe/du/dMbRcsWJAzZ85YvPM4c+YMBQsWfKa2RUREROTlZ1XB+LXXXiMsLMxsvu6dO3c4fPgwxYsXT3afxMREfv/9d4oUKZLi1WKAqlWrEh4eztatW01lZ86c4ciRI1StWjX9TkJEREREXkpWNZWiVq1aBAQE8MEHH9C3b18cHR2ZNGkSDg4OtG7dmkuXLjFw4EAaNmxI/vz5CQ8PZ86cORw6dIixY8eateXv78/rr7/O8OHDAQgODiYkJIRBgwYxYMAAHB0dGTVqFH5+ftSpUycjTldERERErIhVBWMbGxsmTZrEiBEjGDx4MPHx8ZQpU4bZs2fj7e1NWFgYbm5u/Pjjj9y6dQt7e3tKlCjB5MmTqVKlillbCQkJJCYmmpWNHj3a1Pb9+/cJCQnhk08+0bfeiYiIiIh1BWMALy8vvv3222S3eXp68uOPP6aqnePHj1uUZcqUieHDh5uuIouIiIiIJLGqOcYiIiIiIhlFwVhEREREBAVjERERERFAwVhEREREBFAwFhEREREBFIxFRERERAAFYxERERERQMFYRERERARQMBYRERERARSMRUREREQABWMREREREUDBWEREREQEUDAWEREREQEUjEVEREREAAVjERERERFAwVhEREREBFAwFhEREREBFIxFRERERAAFYxERERERQMFYRERERARQMBYRERERARSMRUREREQABWMREREREUDBWEREREQEUDAWEREREQEUjEVEREREADAYjUZjRnfiZbZnzx6MRiMODg7p2u7N25Hcv5+Qrm2KpJWdnS1ZvTJldDdS5XpkJPEJ9zO6GyLY29qRLdPLMW4Awu6Fk5CosSMZz9bGDk9Hj3RtMy4uDoPBQKlSpR5bzy5dj/ovZDAYnku7L0sIEbE2L1MQEbEm6R1ERKyJwWBIVWbTFWMRERERETTHWEREREQEUDAWEREREQEUjEVEREREAAVjERERERFAwVhEREREBFAwFhEREREBFIxFRERERAAFYxERERERQMFYRERERARQMBYRERERARSMRUREREQABWMREREREUDB+F9p7Nix+Pn5mf4rX748rVq1YuPGjRZ1a9SoYVY36b+pU6em2P6iRYvw8/Pj9u3bFtvWrl2Ln58fFy9eTNdzehpHjx5l7NixxMTEmJU/rt9Pa/v27fj5+XHw4MFnbis1ypQpw9ixY1/IscTc8x5PSU6dOsWAAQOoXr06JUqUoHTp0rRs2ZKpU6cSFRX1xP0vXryIn58fv//++2PrJTdGr1y5wscff0yNGjUICAggJCSEjh07smTJkice90VL7fMpL17nzp2pU6cOcXFxZuWHDh3C39+fn3/+2az8zp07fPfddzRo0ICSJUtSsmRJGjVqxFdffWX2+kx6bSf9V7RoUapUqUK/fv24dOnSCzm35IwdO5Y9e/Y8sU5yvxMe/q9GjRovqMeP17RpUwYOHJjR3Xju7DK6A5IxnJycmDlzJgDXr1/np59+onv37syePZtSpUqZ1a1bty6dOnUyK8uVK9cL62t6O3r0KOPGjaNNmzY4OzubyqtXr87cuXNxd3d/5mMUL16cuXPnUqhQoWduS6zf8x5P69ato2/fvhQqVIgePXpQoEABYmJi2LZtGxMmTCAsLIx+/fo9to1s2bIxd+5cChQo8FTnFhERQfPmzfHw8KBXr17kypWLq1evsm3bNjZt2kTTpk2fqj359/rss89o1KgRP/30Ex988AEACQkJDB48GH9/f1q3bm2qe+7cOTp06MD9+/dp164dAQEBGAwGDh8+zK+//srevXuZO3euWfsffvgh5cuXJzExkfPnzzNmzBi6du3K0qVLsbW1faHnCjBu3DhcXFwsfgc87O2336ZKlSqmx/Pnz2f58uWm3ycADg4Oz7WfYk7B+F/KxsaGoKAg0+OSJUtSrVo1fvvtN4tBnDVrVrO6ryovLy+8vLzSpS03N7d/xXMmDzzP8XTjxg3+85//UKZMGSZOnIi9vb1pW7Vq1ejUqRP79+9/bBuxsbE4OTml6TW5evVqrl+/zty5c80CfNOmTUlMTHzq9tIq6Rzk5ZUvXz66devGjz/+SKNGjShYsCCzZs3i2LFjLFiwABub//8Qu1+/fty/f5+FCxeSPXt2U3nFihVp3749S5cutWg/f/78ptd4qVKlcHNz4/333+fMmTMULlz4uZ9fWuTIkYMcOXKYHm/atMni94m8WJpKIQBkz54dLy8vLl++/EKPm/QR2JIlS/j8888pW7YsISEhfP3119y/f9+s7s6dO2nZsiWBgYGUL1+ejz/+mLCwMIu2Fi9ezKBBgyhdujTlypVjxIgRprYWLVrExx9/DDz4Bfvwx1SPTqVIau+3335j8ODBlClThooVKzJ9+nQAVqxYQd26dSlVqhQ9e/YkIiLC1JdHp1I87uOyJEajkalTp1K3bl1KlChBzZo1mTFjhsVztnbtWurVq0dAQABvvfUWBw4ceMZ/BUlv6Tme5s2bx927d/n444/NQnESb29vatWqZXo8duxYgoODOXDgAC1atCAgIIDZs2cnO5UiPj6eL7/8knLlylG6dGkGDRrE3bt3zdoPDw/HxsaGLFmyWBz74SADcPXqVfr370/58uUJDAykTZs2HDp0yKzOb7/9RqtWrShXrhxly5alXbt2Fq/hlM4B4PTp0/Ts2ZNy5cpRsmRJmjRpwvLly832T0xMZOzYsVSqVMn0uyI6OvpxT7O8IO+++y558uRhyJAhXLlyhR9++IG2bdvi7+9vqrNr1y4OHjzIe++9ZxaKkzg4OPDWW2898Viurq4AFn9Lfv31V9Pv2Ro1ajBhwgSLN3nHjx+nc+fOBAUFUbp0aT744AOL8bxgwQIaNmxo+pvUqlUr02s56Xf7N998Y/pdv3379lQ8Q+ZSmpbXo0cP2rVrZ3qcNGaOHz9Oq1atTNNONm3aZNHmokWLaNy4MQEBAVSpUoVRo0aRkJBgVmfPnj288cYbBAQE0KhRo2Snhr2qdMVYALh79y7h4eHkyZPHYpvRaDT7xWIwGNL9Y6nRo0dTs2ZNRo8ezd69exk7diz58uWjVatWwIM5aO+88w7ly5fnhx9+4ObNm3z//fecOnWKX3/91aw/I0eOJCQkhNGjR3PkyBHGjBmDvb09/fv3p3r16rz33nv8+OOPTJkyhUyZMj3xY6rRo0dTp04dfvjhB9auXctXX33F7du32bFjB//5z3+Iiopi2LBhfPvtt3zxxRfJtvHox2X3799n4MCBZv3+8ssvmT9/Pt27d6dkyZLs2bOH7777DkdHR9PzcPToUT744AOqVq3Kxx9/zMWLF+nTp4/FnD3JWOk5nnbs2EH27NkpUqRIqo8fHx9Pv3796NixI3379sXT0zPZeiNHjmTOnDn06tULf39/VqxYwffff29Wp3jx4iQmJtK/f386depEQEAAdnaWfzrCw8Np3bo1Li4ufPrpp2TKlIlZs2bRoUMH1qxZYwrWFy9e5PXXXydfvnzExcWxYsUK2rRpw9KlS/Hx8XnsOZw9e5YWLVqQM2dO/vvf/+Lt7c2JEycsAsvs2bMpXbo0X331FWfPnuWbb74hS5Ys9O/fP9XPoTwfDg4ODBkyhA4dOtCmTRvc3d1N0yqSJAXIkJCQp2o7MTGR+/fvk5iYyIULFxg3bhwFCxY0GzuzZs1i2LBhtGvXjurVq7N3717GjRtHZGQkAwYMAB7MqW/bti158+bl22+/5d69e4waNYq2bduydOlS3Nzc2LlzJ//973/p1KkT1apVIzY2lgMHDhAZGQnA3LlzadGiBe3ataNRo0YAz/2qdXx8PP3796d9+/b06NGDyZMn88EHH7B+/XoyZ84MwPTp0/n222/p0KEDAwcO5PTp06ZgnDQ+bty4QefOnfHz82P06NFEREQwdOhQoqOjKVas2HM9B2ugYPwvlvTH+fr163z77be4urrSvn17i3q//PILv/zyi+mxra0tR44cSde+BAYG8sknnwBQuXJltm/fzurVq02B8KeffsLb25uffvrJdNUsZ86cdO7cmY0bN5rdnJAvXz5GjBgBQJUqVYiNjWX69Om8++67eHl5kS9fPuDBH/zUTJ0ICgpi0KBBAFSoUIE1a9bw888/m/2yOX78OAsWLEgxGD/6cdnnn3/O7du3mT9/PgDnz5/n559/ZujQobRo0QKASpUqERsby/jx42nRogU2NjZMmjSJnDlzMn78eFOYcnR05L///W9qnmZ5jp7XeLp+/To5c+ZM8XhgGa7j4+Pp27cvDRo0MJU9esNrWFgYv/zyC++++y7dunUDHoyXtm3bcu3aNVO9ihUr0rlzZ6ZPn86aNWtwcnKidOnSNGnShKZNm2IwGACYOXMmERERzJ8/3xSCK1asSN26dZk6dSofffQRAD179jS1nZiYSOXKlTlw4ACLFy/mww8/fOw59OvXD3t7e+bMmYObmxvwYJw8ytvb2xTwq1atypEjR1i9erWCsZWoUKECFSpUYNu2bXz33Xemf8sk169fB7B43SckJGA0Gk2PH32D1rdvX7PHuXLlYvLkyaaxkZCQwPjx42nYsKHp701ISAjx8fFMmzaNrl27kjlzZmbMmMH9+/eZNm2a6U1lsWLFaNiwIYsXLzZ9yuHp6WkK0/DgPpUkSVMhcubM+cKmRSQF42rVqgHg4+NDzZo1+euvv2jatClRUVGMGTOGLl26mMZa5cqVsbe356uvvqJz585kzpyZmTNnYjAYmDx5MpkyZQIe/A3r2LHjCzmPjKZg/C8VHR1N8eLFTY9tbW2ZMGECBQsWtKhbv359OnfubHqc9IcwPT16ZaBQoUJs27bN9HjXrl00atTI7KPkkJAQ3N3d2b17t1kwrl27tllbdevWZcKECZw4cYKyZcs+dd8qV65s+tnW1pa8efNiMBhMoRigQIECREREcPfuXdPHdymZN28ev/zyC+PHjzfdnLdlyxYA6tSpYxZ4KlWqxOTJk7ly5Qq5c+dm//791KhRwywE1atXT8E4gz3v8fRondu3b1OxYkXT4yJFilhMJ0j645iSEydOEBsbazFe6tSpw86dO83KPvroI1q1asW6devYvXs3W7duZfPmzWzevJlvv/0WgM2bN1O+fHk8PDxMr2EbGxvKli1r9jHw6dOnGTlyJHv37uXWrVum8rNnz1r08dFz2LZtG3Xr1rUIUo96NCwXKlSIFStWPHYfeXFOnTrF7t27MRgM7Nixg8aNG6dqv6ZNm3Ly5EnT461bt5pd3Ojfvz8VKlTAaDRy/fp1Jk+eTJcuXZg7dy7Zs2cnNDSUO3fuUK9ePbN2GzRowMSJEzlw4ADVqlVj165dlC9f3uyTlkKFClG0aFF2795Nu3bt8Pf3JywsjIEDB9K4cWNKlSpldjN3RrCxsTH7vZAnTx6cnJxMb3T37t1LdHQ09erVs/g7Exsby8mTJylXrhz79++nfPnyplAMD97kpvTJ06tGwfhfysnJiZ9//hmj0cjZs2f5/vvvGTBgAMuWLSNbtmxmdb28vAgICEh120mhLbkbc5LmMT06V/LhAZi0/eHpAREREcnOccySJQvh4eEW/X1Y1qxZgQcfD6VFcn1zcXGxKAO4d+/eY4Pxrl27+Pzzz+nZsyc1a9Y0ld+5cwej0UiFChWS3S8pGN+4ccPieXBzc8PR0fGpzknS1/McT9myZePcuXNmZe7u7ixYsACA8ePHW1wNdnZ2fuIbtKTx8OjrKWm8PCpv3rx07NiRjh07cvfuXXr37s3SpUvp3LkzRYsW5c6dO+zbt8/sDUKSpE9poqKi6NSpE15eXgwcOJBcuXLh6OjIJ598wr179554DmFhYRbPZ3IeXVnm0d8nknGMRiNDhgwhf/78tG7dmi+++II333zT7Kpq0r/xtWvXyJs3r6l81KhRxMbG8ueffzJu3DiLtvPmzWs2tkqVKkXlypWZMWMGAwYMMP2tePQ1n/Q4aXtERESyUwYe/ntTsWJFvvnmG/73v//RuXNnHB0dqVu3LoMGDcqwAOnk5GQxNdDe3t40tu7cuQNAs2bNkt3/ypUrwIPfDfnz57fYnl43p1s7BeN/KRsbG9MvkMDAQHx8fGjevDnjx49n6NChz9R20uC5efOmxR/Z69evY2Nj89S/ODw8PMyuLiW5desWHh4eZmWPrkN88+ZN4MHHqxnpypUrfPDBB1SrVo3333/fbJuHhwcGg4Fffvkl2RuskuZeent7WzwPUVFRFqFCXqznOZ7KlSvHtm3bOH36tOkTBjs7O9PxPD09LYJxaq5CJ42HW7dumd3glDReHsfV1ZXWrVuzadMmQkNDKVq0KB4eHlSpUoXevXtb1E/6Y71v3z6uXr3KxIkTKVq0qGl7ZGSk2VSjlM7B09PT9DG7vJwWLVrErl27mDVrFmXKlGHZsmUMGTKEhQsXmi6qlC9fHoC///7bNJ0OMM0Vfviq8eN4eXmROXNmU/2kvzuP/o1I+p2a9LfkcX9vHl7usGnTpjRt2pTbt2+zbt06RowYgZ2dHcOHD09V/1Ij6aJHfHy8WXlERMRTf3qbdH7jxo2zGG+A6Z6I5P7OgOXz9qrSqhQCQEBAAA0bNmTRokVpvrKapGTJkjg4OLB27VqLbWvXriUwMPCpr3CWLl2adevWmX38s3nzZiIiIihdurRZ3T/++MPs8erVq3F2dsbX1xf4/6u7L/IKUkxMDD169CBz5sx8/fXXFr/Qkj7+CgsLIyAgwOK/pI+OAwMD2bBhg9kdxE/6wgZ58dJzPDVv3hxXV1dGjBhh8cfxWfj6+uLk5GQxXtasWWP2+Pbt22bzOpMkTX1IevNbqVIlU3h/9PWbdId+bGwsYP6J0Z49e1L9JQwVK1Zk9erVqfpCE7E+d+7c4ZtvvqFZs2aULVsWg8HAkCFDOHHiBLNmzTLVK1OmDAEBAfz444/P9Ebo5s2b3LlzxzTtzcfHBy8vL4vfmatWrcLe3p7AwEDgwd+bbdu2mX0aGRoayvHjxy3+3sCDAP72229TuXJlQkNDTeUPX61Nq6QAe/r0aVPZ7du3OXz48FO3FRwcjLOzM1evXk3270zS8xQYGMj27dtNNxLCg2krD68C9SrTFWMx6dGjBytXrmTmzJnPdJOKu7s7nTp1YsKECURHR1OhQgXu3bvHkiVL2LFjB5MmTXrqNrt3707Lli3p1q0b7dq1M61KERgYaDEP8fz583z88cc0aNCAI0eOMGnSJDp06GB6t5x01W327NnUqlULJycns2XTnocRI0Zw/Phxhg8fzqlTp8y2BQUF4ePjQ5s2bfjoo4/o3LkzJUuWJD4+nrNnz7J9+3YmTJgAQNeuXXnrrbd4//33adWqFRcvXmTq1KmaSmGF0ms8eXt7880339C3b19atGhBy5Yt8fHx4d69e5w4cYKtW7cme/XnSTw9PWnZsiWTJ0/GycnJtCrF+fPnzeotXryYJUuW0LRpU/z9/UlMTGTv3r1MnjyZ4sWLm4JCx44dWbZsGW3btqV9+/bkypWL27dvs3//frJnz07Hjh0JCgrCxcWFoUOH0rVrV65du8bYsWOTXZIrOT179uTPP/+kdevWdOnSBW9vb06fPk1MTAzvvvvuUz8H8mJ98803APznP/8xlRUtWpS2bdsyZswY6tevb3otfP/993To0IE33niD9u3bm77g49KlS/z66684ODhYfLp27tw59u3bh9Fo5Nq1a0ydOhWDwUDz5s2BB9P8evTowbBhw/Dy8qJatWrs27ePyZMn06FDB1Mw7NixI4sWLaJTp06899573Lt3j9GjR5MzZ07TNIQxY8YQFhZGuXLlyJIlCydOnGDTpk1mN6gVLFiQdevWUaZMGZydnfHx8Xni/PhH5ciRg5IlSzJ+/HgyZcqEnZ2d2U1xTyNpBZBvv/2Wq1evUq5cOWxtbblw4QLr1q1j7NixODs706FDB9ONue+++y4RERGMHTtWc4zl36dgwYI0aNCAOXPm0K1btzQNvCR9+vTB29ubuXPnMmvWLOzs7ChevDiTJ09+6iV4AEqUKMG0adMYOXIkvXr1wsXFhRo1ajBgwACLpa769u3Ljh076N27N7a2trRu3drsbmV/f3969erF/PnzmTJlCjlz5mT9+vVpPtfUOHPmDAkJCWZ3MCc5fvw4AJ988gk+Pj7MnTuX8ePH4+rqio+Pj9mNIv7+/vzwww9899139OzZkyJFijBq1Cizm7nEOqTneKpVqxaLFi1i8uTJjB8/nlu3buHo6EiRIkVo164dLVu2TFO7/fr1IyEhgSlTppCYmEjt2rXp16+faQUJeHAD3OXLl/ntt99M673mypWLTp068c4775jGX+bMmZk7dy6jR4/mu+++IywsjCxZslCyZEnTDX5Zs2blhx9+4JtvvjF9g9/QoUOZMmVKqvpboEABfv31V77//nuGDh1KQkICBQoUoGvXrmk6f3lxdu3axeLFi/niiy8s5qp+8MEHrFq1ihEjRjB69GjgwZd1LFq0iKlTp7J48WLGjRuHwWAgb968hISEMHLkSIsxNXLkSNPPmTNnpmjRosycOdPsput27dphZ2fHjBkzmDNnDt7e3vTs2ZPu3bub6uTMmZNZs2bxzTff0L9/f2xsbKhcuTIDBw40BduAgABmzpzJqlWriIqKIkeOHHTu3Jn33nvP1M7gwYMZPnw47777LrGxsfzvf/8zTRN5Gt999x2ffPIJH3/8MVmzZqVPnz6sWLHC7IpuanXq1Ins2bMzffp0fv75Z+zs7MiXLx/Vq1c3vdHIli0bkydPZtiwYfTu3Zt8+fIxePBgRo0a9dTHexkZjMl9RibyErp48SI1a9bkhx9+sLjrWERERORJNMdYRERERAQFYxERERERQFMpREREREQAXTEWEREREQEUjEVEREREAAVjERERERFAwVhEREREBFAwFhEREREBFIxFRERERAAFYxERERERQMFYRERERASA/wOfDyxtaIVvgQAAAABJRU5ErkJggg==\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["\n","=== Ringkasan Akurasi ===\n","RF Unoptimized: 73.18%\n","RF GridSearch: 78.41%\n","XGBoost Tuned: 78.41%\n","\n","💡 Interpretasi:\n","- Model dengan akurasi tertinggi adalah: RF GridSearch (78.41%)\n","- Model yang di-'tuning' (GridSearch/Tuned) seringkali memberikan akurasi yang lebih baik.\n","\n","PENTING: Jangan hanya lihat akurasi!\n","Karena data Anda tidak seimbang (banyak 'Normal'), akurasi tinggi bisa menipu.\n","Lihat kembali 'Classification Report' & 'Confusion Matrix' dari Blok 7, 8, 9 untuk memeriksa:\n","  1. Apakah model Anda bisa memprediksi 'Stunting Ringan' & 'Stunting Berat' (Recall > 0)?\n","  2. Atau model Anda hanya 'menebak' semua anak sebagai 'Normal'?\n"]}]}]}