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All Journal Arcitech: Journal of Computer Science and Artificial Intelligence
Elida Silaban
Universitas Negeri Medan
Computer Science & IT

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Analisis Pengelompokan Wilayah Berdasarkan Karakteristik Sosial Ekonomi Menggunakan K-Means dan Simple Additive Weighting (Saw) untuk Penentuan Prioritas Pembangunan di Sumatera Utara Elida Silaban; Chatrine Zefania Manurung
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 6 No. 1 (2026): June 2026
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v6i1.17129

Abstract

Regional development in North Sumatra Province still shows differences in socio-economic conditions between districts/cities, so that objective and data-based development priority determination is needed. This study aims to group regions based on socio-economic characteristics and determine development priorities using the K-Means Clustering and Simple Additive Weighting (SAW) methods. The study used secondary data from the Central Statistics Agency with variables such as poverty rate, open unemployment rate, human development index, life expectancy, average length of schooling, and gross regional domestic product. The results show that the K-Means method produces three regional clusters: developing regions, underdeveloped regions, and developed regions. The underdeveloped region cluster consists of Nias Regency, South Nias, West Nias, and North Nias, while Medan City is the most developed region. The results of the SAW method indicate that West Nias Regency is the main development priority. The integration of the K-Means and SAW methods can produce more structured and objective regional groupings and development priorities.
Co-Authors Chatrine Zefania Manurung