Analysis of the K-Means Method and Segmentation of Open Unemployment Rates in Each Province in Indonesia in 2025

Peniel Sam Putra Sitorus (Universitas HKBP Nommensen Pematangsiantar)
Jaya Tata Hardinata (Universitas HKBP Nommensen Pematangsiantar)
Dudes Manalu (Universitas HKBP Nommensen Pematangsiantar)

JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP)
Vol. 9 No. 1 (2026): Jurnal Teknologi dan Ilmu Komputer Prima (JUTIKOMP)

The Open Unemployment Rate (TPT) is a vital indicator for describing the state of employment in Indonesia. Variations in characteristics across provinces lead to fluctuations in TPT that require systematic analysis. This study aims to analyze and segment Indonesian provinces based on the Open Unemployment Rate using the K-Means clustering method. The data utilized consists of the TPT from 38 provinces in 2025 for the February and August periods. K-Means was applied to group provinces based on similarities in their unemployment rates. The results indicate that provinces can be categorized into several clusters representing low, medium, and high unemployment categories. This segmentation provides an overview of regional unemployment patterns and can serve as a foundation for formulating more targeted labor policies.