Analisis Kesenjangan Pendidikan dan Usia Kerja Masyarakat Kabupaten Garut dengan K-Means Clustering - Hamzah Nurrifqi Fakhri Fikrillah; Fahmi Fadillah Septiana (Institut Teknologi Garut, 2026)
This study aims to analyze educational disparities and working-age populations in Garut Regency using the K-Means Clustering algorithm. The research data comes from the 2024 verification results of the Garut Regency Social Service, comprising 912,419 individuals aged 15 to 60 years. The primary attributes used include age, highest level of education, and occupation, with the optimal number of clusters determined using the Elbow Method (K=3). The analysis results show three main clusters: Cluster 0 (32.4%) consists of individuals in the late productive age group with low education levels and a predominance of informal employment; Cluster 1 (43.6%) consists of young individuals with secondary education, the majority of whom are unemployed; and Cluster 2 (24.0%) consists of individuals in the middle productive age group with secondary education and diverse employment. Model validation yielded a Silhouette Score of 0.5855 and a Davies-Bouldin Index of 0.5188, indicating that the cluster quality is quite good. These findings confirm that education is a key factor in social mobility and access to employment, and can serve as the basis for strategic policies to reduce socioeconomic inequality in Garut Regency.