Penerapan Algoritma K-Means Clustering Pada Pengelompokan Data Pendidikan Tertinggi Angkatan Kerja Menurut Kabupaten/Kota Di Sumatera Utara Tahun 2025

Airin Trisafina Siregar
Citra Dewi Hasibuan
Ema Sri Rezeki

Prosiding Seminar Nasional Official Statistics
Vol 2026 No 1 (2026): Seminar Nasional Official Statistics 2026

The labor force is key to regional economic development. Differences in labor force education reflect variations in human resources, socioeconomic conditions, and labor markets across regions. The objective of this study is to apply k-means clustering to group regions based on the similarity of labor force education level characteristics, specifically uses data on the population of North Sumatra aged 15 and older who are part of the labor force, categorized by regency/city and highest level of education completed (August 2025). The results of this study indicate the formation of two groups: a group with an elementary school education as their highest level of education, and a group dominated by high school graduates