IDENTIFIKASI KEPADATAN PENDUDUK DI PROVINSI JAWA BARAT MENGGUNAKAN HIERARCHICAL CLUSTERING - Simanjuntak, Wahyu Iskandar; Samuel, Yusran Timur (Jurnal Teknoif Teknik Informatika Institut Teknologi Padang, 2025)
This research applies a hierarchical clustering algorithm to identify population density patterns in West Java (18 regencies, 9 cities) as a basis for natural disaster management. Population density data for 2020-2022 from the West Java Population Office was analyzed to group areas into three categories: densest, medium, and lowest. The hierarchical clustering method was used to group areas based on population density and flood potential, with the additional attribute of river presence. The clustering results were evaluated using the Davies-Bouldin index. The results showed that the algorithm was successfully applied, grouping 20 districts/cities with the lowest population density (Cluster 0), 3 districts/cities with medium density (Cluster 1), and 4 districts/cities with the densest density (Cluster 2).This research is expected to provide insight to the government and related institutions in planning disaster mitigation based on population density patterns, so as to reduce the risk of natural disasters in the future. This research takes data from the official source https://jabar.bps.go.id/indicator/12/245/1/kepadatan-penduduk-menurut-kabupaten-kota.html. The main objective of this research is to understand population density patterns that can provide an indication of the level of risk to certain natural disasters in the West Java region. This information is expected to be used as a basis for more effective and efficient disaster management strategies in the future. The implication of this research shows that by understanding the pattern of population density and river distribution through the hierarchical clustering method, the government and related institutions can formulate more targeted disaster management strategies.