Analisis Disparitas Sosial-Ekonomi Antarprovinsi di Indonesia Menggunakan Pendekatan K-Means Clustering
DOI:
https://doi.org/10.63822/p3gk1679Keywords:
K-Means; socio-economic disparities; human development; unemployment; povertyAbstract
Socio-economic disparities across provinces remain an important issue in regional development due to differences in human development, labor market conditions, and poverty levels. This study aims to analyze socio-economic disparities across 38 provinces in Indonesia in 2025 using the K-Means clustering approach. Secondary data from Statistics Indonesia (BPS) were analyzed using three indicators: Human Development Index (HDI), Open Unemployment Rate (OUR), and percentage of poor population. The data were standardized using Z-score transformation, while the optimal number of clusters was determined using the Elbow Method and Silhouette Score. The results identified two clusters as the best configuration, with the highest Silhouette Score of 0.4961. Cluster 0 comprised 33 provinces with average HDI, OUR, and poverty rates of 75.70, 4.62%, and 8.40%, respectively. Cluster 1 comprised five provinces with averages of 64.69, 3.44%, and 22.60%, respectively. Principal Component Analysis showed that the first two components explained 94.40% of the total variance. These findings reveal distinct socio-economic typologies across Indonesian provinces and highlight the importance of multidimensional and differentiated regional development strategies.
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