{
"cells": [
{
"cell_type": "markdown",
"id": "fc554312",
"metadata": {},
"source": [
"# 04 — GIS & Spatial Analytics\n",
"\n",
"**Exact-code spatial join, Queen adjacency, dan permutation test**\n",
"\n",
"Notebook ini adalah POC portfolio yang dapat dijalankan ulang dari artefak lokal Pasuruan Lens. Kode produksi tetap berada di `python/scripts/` dan `python/src/pasuruan365/`; notebook berfungsi sebagai narasi analitik yang ringkas, transparan, dan mudah dipresentasikan."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "266d21d5",
"metadata": {
"execution": {
"iopub.execute_input": "2026-09-04T06:27:31.159299Z",
"iopub.status.busy": "2026-09-04T06:27:31.159133Z",
"iopub.status.idle": "2026-09-04T06:27:32.949184Z",
"shell.execute_reply": "2026-09-04T06:27:32.948149Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Project root: PASURUAN365\n",
"Python: 3.12.6\n"
]
}
],
"source": [
"from pathlib import Path\n",
"import json\n",
"import sys\n",
"\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"\n",
"\n",
"def find_project_root(start: Path | None = None) -> Path:\n",
" start = (start or Path.cwd()).resolve()\n",
" for candidate in (start, *start.parents):\n",
" if (candidate / \"package.json\").exists() and (candidate / \"data\").exists():\n",
" return candidate\n",
" raise RuntimeError(\"Root Pasuruan Lens tidak ditemukan. Jalankan notebook dari repository ini.\")\n",
"\n",
"\n",
"ROOT = find_project_root()\n",
"sys.path.insert(0, str(ROOT / \"python\" / \"src\"))\n",
"\n",
"pd.set_option(\"display.max_columns\", 100)\n",
"pd.set_option(\"display.max_colwidth\", 100)\n",
"sns.set_theme(style=\"whitegrid\", context=\"notebook\")\n",
"COLORS = {\"A\": \"#2563eb\", \"B\": \"#f59e0b\", \"C\": \"#10b981\"}\n",
"\n",
"print(f\"Project root: {ROOT}\")\n",
"print(f\"Python: {sys.version.split()[0]}\")"
]
},
{
"cell_type": "markdown",
"id": "42dd872f",
"metadata": {},
"source": [
"## Tujuan\n",
"\n",
"Geometri dipakai sebagai konteks analitik setelah model selesai. Lokasi, kecamatan, dan adjacency tidak dimasukkan ke clustering. Dengan begitu, pola spasial berfungsi sebagai bukti deskriptif eksternal—bukan target yang secara otomatis dipaksakan oleh model."
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "6a287d38",
"metadata": {
"execution": {
"iopub.execute_input": "2026-09-04T06:27:32.955570Z",
"iopub.status.busy": "2026-09-04T06:27:32.955171Z",
"iopub.status.idle": "2026-09-04T06:27:34.660255Z",
"shell.execute_reply": "2026-09-04T06:27:34.659674Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" nilai | \n",
"
\n",
" \n",
" \n",
" \n",
" | polygon | \n",
" 365 | \n",
"
\n",
" \n",
" | unique GIS ID | \n",
" 365 | \n",
"
\n",
" \n",
" | matched assignment | \n",
" 365 | \n",
"
\n",
" \n",
" | CRS browser | \n",
" EPSG:4326 | \n",
"
\n",
" \n",
" | Queen directed edges | \n",
" 2084 | \n",
"
\n",
" \n",
"
\n",
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"mapped = geo.merge(assignments[[\"village_id\", \"cluster_label\"]], on=\"village_id\", validate=\"one_to_one\")\n",
"mapped[\"typology\"] = mapped.cluster_label.str.replace(\"Typology \", \"\", regex=False)\n",
"\n",
"fig, ax = plt.subplots(figsize=(9, 9))\n",
"mapped.plot(color=mapped[\"typology\"].map(COLORS), edgecolor=\"white\", linewidth=.18, ax=ax)\n",
"ax.set_title(\"Pasuruan Lens — tipologi pada 365 poligon BIG\")\n",
"ax.set_axis_off()\n",
"plt.tight_layout()"
]
},
{
"cell_type": "markdown",
"id": "3e7a0b22",
"metadata": {},
"source": [
"## POC 2 — Hitung ulang same-type adjacency"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "02d647a1",
"metadata": {
"execution": {
"iopub.execute_input": "2026-09-04T06:27:35.352177Z",
"iopub.status.busy": "2026-09-04T06:27:35.351893Z",
"iopub.status.idle": "2026-09-04T06:27:35.393472Z",
"shell.execute_reply": "2026-09-04T06:27:35.393024Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" nilai | \n",
"
\n",
" \n",
" \n",
" \n",
" | unique Queen edges | \n",
" 1042.000000 | \n",
"
\n",
" \n",
" | observed from data | \n",
" 0.566219 | \n",
"
\n",
" \n",
" | published observed | \n",
" 0.566219 | \n",
"
\n",
" \n",
" | published expected | \n",
" 0.376074 | \n",
"
\n",
" \n",
" | published p-value | \n",
" 0.001000 | \n",
"
\n",
" \n",
"
\n",
"