Hilma Mutiara Winata
Department of Public Administration, Faculty of Social and Political Sciences, Sunan Gunung Djati State Islamic University, Bandung, Indonesia, 40614

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Regional development in West Java Province: Clustering population density, human development index, and life expectancy Weky Agesty; Nayla Bunga Safa Felisa; Aulia Sri Barokah; Hilma Mutiara Winata
Tamalanrea: Journal of Government and Development (JGD) Vol. 3 No. 1 (2026): APRIL 2026
Publisher : Department of Government Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69816/jgd.v3i1.48775

Abstract

This study investigates regional development patterns in West Java Province by examining the relationships among population density, the Human Development Index (HDI), and life expectancy, while also identifying regional characteristics through K-means clustering analysis. The study aims to provide a comprehensive overview of these indicators, evaluate their linear relationships, and classify districts and municipalities according to their development profiles. A quantitative research approach was employed, utilizing descriptive statistics, Pearson’s correlation analysis, and K-means clustering. Secondary data were obtained from official government publications. The findings reveal a strong positive correlation between population density and HDI, as well as between population density and life expectancy. The clustering analysis identified two distinct groups: highly urbanized and densely populated areas characterized by higher HDI scores and longer life expectancy, and less densely populated districts exhibiting comparatively lower levels of human development. These results underscore persistent disparities in regional development between urban and non-urban areas in West Java, which are associated with unequal access to education, healthcare services, and infrastructure. The study provides empirical evidence that can support regional governments in designing more targeted and equitable development policies tailored to the specific characteristics and needs of each cluster.