PENERAPAN MULTI-CLUSTERING DALAM PENGELOMPOKAN KABUPATEN/KOTA DI PROVINSI JAWA BARAT BERDASARKAN INDEKS DESA MEMBANGUN - Nur Khamidah; Reka Agustia Astari; Anwar Fitrianto; Erfiani Erfiani; Alfa Nugraha Pradana (Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika, 2023)
Cluster analysis is a statistical learning technique that aims to uncover hidden patterns in data by grouping it based on known explanatory variables. In multi-clustering algorithms, similar data in different sub-dimensions of categories are initially grouped separately and then re-categorized based on the obtained clusters, resulting in a more exploratory grouping. This research aims to conduct exploratory analysis of regencies/cities in West Java based on the Village Development Index (Indeks Desa Membangun/IDM), which consists of three sub-dimensions: Social Resilience Index, Economic Index, and Environmental Index. It also aims to observe how the regencies/cities in West Java are grouped based on these indices using a multi-clustering algorithm with KMeans for each sub-dimension. From the exploration and analysis results, regencies/cities are clustered based on the three sub-dimensions. Additionally, recommendations are obtained suggesting that the equal distribution of educational facilities, addressing crime rates, improving economic infrastructure, and enhancing environmental quality should be priorities for the government of West Java province