Application of Fuzzy C-Means with Variations in Weighting Exponent for Clustering the Human Development Index - Indah Suciati; Rian Kurnia; Vina Nurmadani; Fitri Nurjanah (Universitas Muhammadiyah Metro, 2026)
Human development is commonly measured using the Human Development Index (HDI), which reflects the quality of life across regions. In Indonesia, disparities in HDI values indicate uneven development, requiring appropriate analytical approaches. This study aims to cluster Indonesian provinces based on HDI indicators using the Fuzzy C-Means (FCM) method with variations in the weighting exponent. The data consist of 38 provinces in 2025, including life expectancy, expected years of schooling, average years of schooling, and adjusted real expenditure per capita. The clustering results were evaluated using the Partition Coefficient Index (PCI). The optimal configuration was obtained at and , with a PCI value of 0.716399. The results show that provinces are grouped into clusters with relatively lower HDI, which are predominantly located in eastern Indonesia, and clusters with higher HDI, which are mostly found in western Indonesia. These findings demonstrate that FCM is effective in identifying regional development patterns.