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Sagita Maesarah
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PENERAPAN K-MEANS CLUSTERING UNTUK PENGELOMPOKAN WILAYAH BERDASARKAN TINGKAT KEMISKINAN DI INDONESIA Sagita Maesarah; Zaehol Fatah
Jurnal Ilmiah Multidisiplin Ilmu Vol. 1 No. 6 (2024): Desember : Jurnal Ilmiah Multidisiplin Ilmu (JIMI)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/3d5mkb02

Abstract

Poverty is one of the problems that hinder national and regional growth. Poverty is the inability to meet the minimum standards of basic needs including food and non-food needs. Poor people are people who are below a limit or called the poverty line. The resources used are sourced from www.kaggle.com. In the process of data processing with the k-means Clustering method. The K-means Clustering method is a method of grouping existing data into several groups where the data in one group has the same characteristics as each other and has different characteristics from the data in the group. The results of the study show that regions in Indonesia can be grouped into several clusters with different poverty level characteristics. These clusters reveal specific patterns, such as the concentration of areas with high poverty in certain areas and the factors that contribute to these conditions. With this approach, the government and policy makers can identify priority areas and design more effective programs to reduce poverty levels..
Co-Authors Zaehol Fatah