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Journal : International Journal of Computer and Information System (IJCIS)

Identifying Regional Patterns of Poverty in Indonesia: a Clustering Approach Using K-Means Wahyuni, Sri; Hananto, Agustia; Huda, Baenil; Apriani, Fitria; Tukino, Tukino
International Journal of Computer and Information System (IJCIS) Vol 6, No 1 (2025): IJCIS : Vol 6 - Issue 1 - 2025
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v6i1.218

Abstract

Poverty in Indonesia remains a major challenge, with significant levels of inequality between provinces. This study applies the K-Means clustering method to analyze poverty distribution patterns in 38 provinces in Indonesia, using data on the percentage of poor people from 2010 to 2024. With this approach, provinces are grouped into three main clusters: low, medium, and high, based on the average poverty rate. The low cluster includes areas with poverty rates below 10%, while the medium and high clusters indicate poverty levels that require more specific policies. The evaluation results show a silhouette score of 0.613, indicating that this grouping is quite good but can still be improved. This study offers important insights to support more targeted and effective policies, especially in achieving Sustainable Development Goal (SDG) 1: Eradicating Poverty.