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All Journal UNP Journal of Statistics and Data Science
Fadhira Vitasya Putri
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Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Social Sciences

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Fuzzy C-Means Based Clustering of Central Java’s Regencies and Cities Using Economic Welfare Indicators 2023 Winda Fariza, Winda Fariza; Syafriandi Syafriandi; Fadhira Vitasya Putri; Eujeniatul Jannah
UNP Journal of Statistics and Data Science Vol. 3 No. 4 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss4/414

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.
Co-Authors Eujeniatul Jannah Syafriandi Syafriandi Winda Fariza, Winda Fariza