Density-Based Spatial Clustering for Assessing Public Service Accessibility in Jombang Regency
Abstract
The problem of unequal accessibility to public services between subdistricts in Jombang can hinder medium, long-term equitable development. Good accessibility indicates justice and improvements in quality of life in the area. In some subdistricts, school and health facilities are easy to reach, whereas in other areas, mountainous regions or border areas, accessibility is very low. This study aims to map accessibility clusters, analyze the data, and provide recommendations for priority intervention area using DBSCAN. The variables include population density, ratios of health facility, education and administrative facilities per area, geospatial public datasets such as road network density, elevation/slope and rivers. The results show three accessibility clusters (high, medium, and low) with variations in geographical constraints such as hills and major rivers that affect the distribution of services. The visualization shows that low-accessibility areas are generally located in peripheral and mountainous regions, whereas high accessibility is concentrated in the regency center.
Keywords: DBSCAN; Spatial clustering; Public service accessibility; Geospatial
Abstrak
Permasalahan ketimpangan aksesibilitas layanan publik antar kecamatan di Jombang dapat menghambat pemerataan pembangunan jangka menengah dan jangka panjang. Aksesibilitas yang baik mengindikasikan keadilan dan peningkatan kualitas hidup di wilayah tersebut. Di beberapa kecamatan, fasilitas sekolah dan kesehatan mudah dijangkau, sedangkan di daerah lain, pegunungan atau perbatasan, aksesibilitas sangat rendah. Kondisi ini menunjukkan adanya ketimpangan spasial yang perlu dianalisis lebih lanjut. Penelitian ini bertujuan untuk memetakan cluster aksesibilitas, menganalisis data hasil dan memberi rekomendasi lokasi prioritas intervensi. Clustering ini menggunakan metode DBSCAN. Variabel mencakup kepadatan penduduk, rasio fasilitas kesehatan, pendidikan, administrasi per wilayah, geospasial public dataset berupa kepadatan jaringan jalan, hambatan seperti elevasi/lereng dan sungai besar. Hasilnya terdapat tiga klaster aksesibilitas, yaitu tinggi, menengah, dan rendah, dengan variasi hambatan geografis seperti perbukitan dan sungai besar yang memengaruhi distribusi layanan. Visualisasi memperlihatkan bahwa daerah aksesibilitas rendah umumnya berada di wilayah pinggiran dan pegunungan, sedangkan aksesibilitas tinggi terkonsentrasi di pusat kabupaten.
Kata kunci: DBSCAN; Spasial clustering; Aksesibilitas layanan public; Geospasial
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