309 lines
125 KiB
Plaintext
309 lines
125 KiB
Plaintext
{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"colab": {
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"provenance": []
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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},
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"language_info": {
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"name": "python"
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}
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},
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/",
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"height": 1000
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},
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"id": "cQBJpfhL37Xb",
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"outputId": "8fcae14d-bf39-4f29-87dd-e622f2dfc338"
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},
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"outputs": [
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{
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"output_type": "display_data",
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"data": {
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"text/plain": [
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"<Figure size 1200x600 with 1 Axes>"
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],
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"image/png": 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\n"
|
|
},
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"name": "stdout",
|
|
"text": [
|
|
"============================================================\n",
|
|
"EVALUASI HIERARCHICAL CLUSTERING\n",
|
|
"============================================================\n",
|
|
"Silhouette Score : 0.599\n",
|
|
"Davies-Bouldin Index : 0.460\n",
|
|
"\n",
|
|
"Ringkasan Statistik per Cluster:\n",
|
|
"\n",
|
|
"| cluster | wilayah | pendidik_avg | sekolah_avg | rasio_avg |\n",
|
|
"|:-----------------|:----------|:---------------|:--------------|:------------|\n",
|
|
"| Kepadatan Sedang | 9 | 8944.44 | 323.33 | 27.13 |\n",
|
|
"| Kepadatan Tinggi | 3 | 22666.7 | 800 | 28.28 |\n",
|
|
"| Kepadatan Rendah | 12 | 3500 | 156.67 | 21.95 |\n",
|
|
"\n",
|
|
"Wilayah dalam setiap Cluster:\n",
|
|
" • Cluster 0 (Kepadatan Sedang): DKI Jakarta, Sumatera Utara, Banten, Sulawesi Selatan, Bali, Lampung, Riau, Aceh, Sumatera Barat\n",
|
|
" • Cluster 1 (Kepadatan Tinggi): Jawa Barat, Jawa Tengah, Jawa Timur\n",
|
|
" • Cluster 2 (Kepadatan Rendah): Kalimantan Timur, Papua, Maluku, NTB, Sulawesi Utara, Kalimantan Selatan, Jambi, Bengkulu, NTT, Papua Barat, Gorontalo, Maluku Utara\n"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "display_data",
|
|
"data": {
|
|
"text/plain": [
|
|
"<Figure size 800x600 with 1 Axes>"
|
|
],
|
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"image/png": 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\n"
|
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},
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"output_type": "stream",
|
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"name": "stdout",
|
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"text": [
|
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"Hasil clustering disimpan ke: hasil_hierarchical_pendidik_sma_2024.csv\n"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "display_data",
|
|
"data": {
|
|
"text/plain": [
|
|
"<IPython.core.display.Javascript object>"
|
|
],
|
|
"application/javascript": [
|
|
"\n",
|
|
" async function download(id, filename, size) {\n",
|
|
" if (!google.colab.kernel.accessAllowed) {\n",
|
|
" return;\n",
|
|
" }\n",
|
|
" const div = document.createElement('div');\n",
|
|
" const label = document.createElement('label');\n",
|
|
" label.textContent = `Downloading \"${filename}\": `;\n",
|
|
" div.appendChild(label);\n",
|
|
" const progress = document.createElement('progress');\n",
|
|
" progress.max = size;\n",
|
|
" div.appendChild(progress);\n",
|
|
" document.body.appendChild(div);\n",
|
|
"\n",
|
|
" const buffers = [];\n",
|
|
" let downloaded = 0;\n",
|
|
"\n",
|
|
" const channel = await google.colab.kernel.comms.open(id);\n",
|
|
" // Send a message to notify the kernel that we're ready.\n",
|
|
" channel.send({})\n",
|
|
"\n",
|
|
" for await (const message of channel.messages) {\n",
|
|
" // Send a message to notify the kernel that we're ready.\n",
|
|
" channel.send({})\n",
|
|
" if (message.buffers) {\n",
|
|
" for (const buffer of message.buffers) {\n",
|
|
" buffers.push(buffer);\n",
|
|
" downloaded += buffer.byteLength;\n",
|
|
" progress.value = downloaded;\n",
|
|
" }\n",
|
|
" }\n",
|
|
" }\n",
|
|
" const blob = new Blob(buffers, {type: 'application/binary'});\n",
|
|
" const a = document.createElement('a');\n",
|
|
" a.href = window.URL.createObjectURL(blob);\n",
|
|
" a.download = filename;\n",
|
|
" div.appendChild(a);\n",
|
|
" a.click();\n",
|
|
" div.remove();\n",
|
|
" }\n",
|
|
" "
|
|
]
|
|
},
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"output_type": "display_data",
|
|
"data": {
|
|
"text/plain": [
|
|
"<IPython.core.display.Javascript object>"
|
|
],
|
|
"application/javascript": [
|
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"download(\"download_0e2fb71a-d1cc-496d-bc67-bd040be32639\", \"hasil_hierarchical_pendidik_sma_2024.csv\", 1243)"
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]
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},
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"metadata": {}
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},
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"============================================================\n",
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"ANALISIS HIERARCHICAL CLUSTERING SELESAI\n",
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"============================================================\n"
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]
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}
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],
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"source": [
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"# Hierarchical Clustering: Jumlah Pendidik SMA 2024\n",
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"# Analisis Pengelompokan Wilayah Berdasarkan Data Pendidik\n",
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"\n",
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"# ==========================================\n",
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"# 1. IMPORT LIBRARY\n",
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"# ==========================================\n",
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"import pandas as pd\n",
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"import seaborn as sns\n",
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"from sklearn.preprocessing import StandardScaler\n",
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"from sklearn.cluster import AgglomerativeClustering\n",
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"from sklearn.metrics import silhouette_score, davies_bouldin_score\n",
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"from scipy.cluster.hierarchy import dendrogram, linkage\n",
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"import warnings\n",
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"from google.colab import files\n",
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"\n",
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"warnings.filterwarnings('ignore')\n",
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"plt.style.use('seaborn-v0_8-darkgrid')\n",
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"sns.set_palette(\"husl\")\n",
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"\n",
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"# ==========================================\n",
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"# 2. LOAD DATA\n",
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"# ==========================================\n",
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"data_contoh = {\n",
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" 'wilayah': ['DKI Jakarta', 'Jawa Barat', 'Jawa Tengah', 'Jawa Timur',\n",
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" 'Sumatera Utara', 'Banten', 'Sulawesi Selatan', 'Kalimantan Timur',\n",
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" 'Papua', 'Maluku', 'Bali', 'NTB', 'Lampung', 'Riau',\n",
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" 'Sulawesi Utara', 'Kalimantan Selatan', 'Jambi', 'Bengkulu',\n",
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" 'Aceh', 'Sumatera Barat', 'NTT', 'Papua Barat', 'Gorontalo', 'Maluku Utara'],\n",
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" 'jumlah_pendidik': [15000, 25000, 20000, 23000, 12000, 10000, 8000, 5000,\n",
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" 3000, 2500, 6000, 4500, 7000, 6500, 4000, 5500, 4200, 3500,\n",
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" 8500, 7500, 3800, 2000, 1800, 2200],\n",
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" 'jumlah_sekolah': [450, 850, 750, 800, 400, 350, 300, 200,\n",
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" 150, 120, 250, 180, 280, 260, 170, 220, 190, 160,\n",
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" 320, 300, 190, 100, 90, 110]\n",
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"}\n",
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"\n",
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"df = pd.DataFrame(data_contoh)\n",
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"df['rasio_guru_per_sekolah'] = df['jumlah_pendidik'] / df['jumlah_sekolah']\n",
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"\n",
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"# ==========================================\n",
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"# 3. PERSIAPAN DATA\n",
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"# ==========================================\n",
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"features = ['jumlah_pendidik', 'jumlah_sekolah']\n",
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"X = df[features].values\n",
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"scaler = StandardScaler()\n",
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"X_scaled = scaler.fit_transform(X)\n",
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"\n",
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"# ==========================================\n",
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"# 4. DENDROGRAM (MENENTUKAN JUMLAH CLUSTER)\n",
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"# ==========================================\n",
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"plt.figure(figsize=(12, 6))\n",
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"linked = linkage(X_scaled, method='ward')\n",
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"dendrogram(linked,\n",
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" labels=df['wilayah'].values,\n",
|
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" orientation='top',\n",
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" distance_sort='descending',\n",
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" show_leaf_counts=True)\n",
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"plt.title('Dendrogram Hierarchical Clustering')\n",
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"plt.xlabel('Wilayah')\n",
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"plt.ylabel('Jarak')\n",
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"plt.xticks(rotation=90)\n",
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"plt.tight_layout()\n",
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"plt.show()\n",
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"\n",
|
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"# ==========================================\n",
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"# 5. IMPLEMENTASI HIERARCHICAL CLUSTERING\n",
|
|
"# ==========================================\n",
|
|
"optimal_cluster = 3\n",
|
|
"hc = AgglomerativeClustering(n_clusters=optimal_cluster, metric='euclidean', linkage='ward')\n",
|
|
"df['cluster'] = hc.fit_predict(X_scaled)\n",
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"\n",
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|
"# ==========================================\n",
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"# 6. EVALUASI CLUSTERING\n",
|
|
"# ==========================================\n",
|
|
"s_score = silhouette_score(X_scaled, df['cluster'])\n",
|
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"db_score = davies_bouldin_score(X_scaled, df['cluster'])\n",
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"\n",
|
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"print(\"=\"*60)\n",
|
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"print(\"EVALUASI HIERARCHICAL CLUSTERING\")\n",
|
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"print(\"=\"*60)\n",
|
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"print(f\"Silhouette Score : {s_score:.3f}\")\n",
|
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"print(f\"Davies-Bouldin Index : {db_score:.3f}\")\n",
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"\n",
|
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"# ==========================================\n",
|
|
"# 7. ANALISIS HASIL CLUSTERING\n",
|
|
"# ==========================================\n",
|
|
"cluster_labels = {}\n",
|
|
"avg_pendidik = df.groupby('cluster')['jumlah_pendidik'].mean()\n",
|
|
"\n",
|
|
"for i in range(optimal_cluster):\n",
|
|
" if avg_pendidik[i] > 15000:\n",
|
|
" cluster_labels[i] = 'Kepadatan Tinggi'\n",
|
|
" elif avg_pendidik[i] > 7000:\n",
|
|
" cluster_labels[i] = 'Kepadatan Sedang'\n",
|
|
" else:\n",
|
|
" cluster_labels[i] = 'Kepadatan Rendah'\n",
|
|
"\n",
|
|
"df['label_cluster'] = df['cluster'].map(cluster_labels)\n",
|
|
"\n",
|
|
"summary = df.groupby('cluster').agg(\n",
|
|
" wilayah=('wilayah', 'count'),\n",
|
|
" pendidik_avg=('jumlah_pendidik', 'mean'),\n",
|
|
" sekolah_avg=('jumlah_sekolah', 'mean'),\n",
|
|
" rasio_avg=('rasio_guru_per_sekolah', 'mean')\n",
|
|
").round(2).rename(index=cluster_labels)\n",
|
|
"\n",
|
|
"print(\"\\nRingkasan Statistik per Cluster:\\n\")\n",
|
|
"print(summary.to_markdown(numalign=\"left\", stralign=\"left\"))\n",
|
|
"\n",
|
|
"print(\"\\nWilayah dalam setiap Cluster:\")\n",
|
|
"for i in range(optimal_cluster):\n",
|
|
" wilayah_list = df[df['cluster'] == i]['wilayah'].values\n",
|
|
" print(f\" • Cluster {i} ({cluster_labels[i]}): {', '.join(wilayah_list)}\")\n",
|
|
"\n",
|
|
"# ==========================================\n",
|
|
"# 8. VISUALISASI HASIL CLUSTERING\n",
|
|
"# ==========================================\n",
|
|
"plt.figure(figsize=(8, 6))\n",
|
|
"sns.scatterplot(data=df,\n",
|
|
" x='jumlah_sekolah',\n",
|
|
" y='jumlah_pendidik',\n",
|
|
" hue='label_cluster',\n",
|
|
" style='label_cluster',\n",
|
|
" s=150,\n",
|
|
" palette='viridis',\n",
|
|
" edgecolor='black')\n",
|
|
"plt.title('Hierarchical Clustering: Pendidik vs Sekolah')\n",
|
|
"plt.xlabel('Jumlah Sekolah')\n",
|
|
"plt.ylabel('Jumlah Pendidik')\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.show()\n",
|
|
"\n",
|
|
"# ==========================================\n",
|
|
"# 9. EXPORT HASIL\n",
|
|
"# ==========================================\n",
|
|
"hasil_df = df[['wilayah', 'jumlah_pendidik', 'jumlah_sekolah',\n",
|
|
" 'rasio_guru_per_sekolah', 'cluster', 'label_cluster']].sort_values('cluster')\n",
|
|
"\n",
|
|
"hasil_df.to_csv('hasil_hierarchical_pendidik_sma_2024.csv', index=False)\n",
|
|
"print(\"Hasil clustering disimpan ke: hasil_hierarchical_pendidik_sma_2024.csv\")\n",
|
|
"\n",
|
|
"try:\n",
|
|
" files.download('hasil_hierarchical_pendidik_sma_2024.csv')\n",
|
|
"except:\n",
|
|
" print(\"Auto-download hanya berfungsi di Google Colab\")\n",
|
|
"\n",
|
|
"print(\"=\"*60)\n",
|
|
"print(\"ANALISIS HIERARCHICAL CLUSTERING SELESAI\")\n",
|
|
"print(\"=\"*60)"
|
|
]
|
|
}
|
|
]
|
|
} |