Fuzzy C-Means Based Clustering of Central Java’s Regencies and Cities Using Economic Welfare Indicators 2023

Abstract

This study aims to cluster the regencies and cities in Central Java Province based on economic welfare indicators using the Fuzzy C-Means (FCM) method. The motivation for this research arises from the evident disparities in development outcomes across regions in Indonesia, particularly in Central Java. Several areas in this province continue to experience high poverty rates, low income, and poor human development despite improvements in labor force participation in others. Five key indicators were used: Labor Force Participation Rate (TPAK), Open Unemployment Rate (TPT), Percentage of Poor Population (PPM), Average Net Income (RPB), and Human Development Index (HDI). The data, obtained from Badan Pusat Statistik (2023), were standardized and analyzed using the FCM algorithm with optimal clusters determined via the elbow method. The clustering results show three distinct regional groupings: Cluster 0 includes areas with relatively high HDI and income despite lower labor participation and higher poverty; Cluster 1 comprises urbanized areas with high labor participation but lower HDI; and Cluster 2 represents the most disadvantaged areas with low income, high unemployment, and poor development outcomes. These findings offer a valuable foundation for targeted policy interventions and strategic regional development planning. Fuzzy C-Means proves to be an effective approach for uncovering nuanced regional profiles in socio-economic development.