Analisis Klaster Kabupaten/Kota di Jawa Barat Berdasarkan Karakteristik Sosial Ekonomi Terkait Pengangguran Menggunakan K-Means
Keywords:
Unemployment, clustering, K-Means, GRDP, LFPR, education, population density, evidence-based policy, West JavaAbstract
Unemployment remains a major issue in West Java Province, which exhibits substantial socio-economic diversity. This study aims to cluster regencies/cities based on socio-economic characteristics associated with labor market conditions, analyze the characteristics of each cluster, and formulate relevant evidence-based employment policy recommendations. A quantitative descriptive approach with K-Means cluster analysis was employed, using secondary data on the Labor Force Participation Rate (LFPR), Gross Regional Domestic Product (GRDP) per capita, Average Years of Schooling, and Population Density. The analysis identified two clusters: Cluster 0 consists of non-metropolitan regions with medium GRDP, low population density, and moderate schooling levels; Cluster 1 comprises metropolitan or urban areas with high GRDP, high population density, and higher schooling attainment. Based on these cluster characteristics, evidence-based policy recommendations were formulated to support employment expansion tailored to regional contexts. This study highlights the importance of data-driven approaches in developing effective, targeted, and inclusive employment policies.
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