Pemetaan Kinerja Pendidikan Provinsi di Indonesia Menggunakan Algoritma K-Means Berdasarkan Indikator Pendidikan Tahun 2025 - Sutan M Arif; Indah Pangesti; Fadjriah Hapsari (Educational Journal, 2026)
Education is one of the key indicators in measuring the quality of human resources and regional development. This study aims to map the educational performance of provinces in Indonesia using the K-Means clustering algorithm based on three educational indicators, namely Average Years of Schooling (AYS), Expected Years of Schooling (EYS), and School Participation Rate (SPR) for the 16–18 age group in 2025. The study employed a quantitative approach using secondary data obtained from Statistics Indonesia (BPS), covering 38 provinces. Data were processed through descriptive statistical analysis, Z-score normalization, determination of the optimal number of clusters using the Elbow Method, clustering with the K-Means algorithm, and cluster quality evaluation using the Silhouette Score. The results identified three clusters representing high, moderate, and low educational performance. Most provinces were classified into the moderate-performance cluster, while a small number of provinces belonged to the low-performance cluster. The Silhouette Score of 0.453 indicates that the clustering results have acceptable quality and adequately represent the characteristics of educational performance across provinces. The findings provide useful information for supporting educational planning and policy formulation to reduce regional disparities in Indonesia.