Fuzzy geographically weighted clustering pada pengelompokan kabupaten/kota di Kalimantan berdasarkan indikator indeks pembangunan manusia - Milda Alfitri Diani; Memi Nor Hayati; Rito Goejantoro (Mandalika Mathematics and Educations Journal, 2025)
Fuzzy Geographically Weighted Clustering (FGWC) is a method of development of fuzzy clustering by considering geographical elements in the process of regional clustering. This study aims to identify the number and characteristics of optimal clusters formed using the FGWC algorithm with the validity index of the Partition Coefficient Index (PCI). The data analyzed includes HDI indicators for all regencies/cities on the island of Kalimantan in 2024 consisting of the variables Life Expectancy, Length of Schooling, Average School Length, Expenditure per Capita, Open Unemployment Rate, and Percentage of Poor Population. Based on the results of the study, the optimal number of clusters was obtained as many as 2 clusters with a PCI of 0.516. Cluster 1 consists of 18 regencies/cities covering 9 cities and 9 regencies with higher average values of HDI indicator variables, while cluster 2 consists of 38 regencies which are all dominated by inland areas with lower average values of HDI indicator variables.