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All Journal Journal of Big Data Analytic and Artificial Intelligence
Anugrah Suseno, Lorencia
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Computer Science & IT

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Klasifikasi Kemiskinan Kabupaten dan Kota di Indonesia Berdasarkan Indikator Sosial Ekonomi Menggunakan Algoritma C4.5 Anugrah Suseno, Lorencia; Basami Hutapea, Tio; Kurniawan, Arga
Journal of Big Data Analytic and Artificial Intelligence Vol 8 No 2 (2025): JBIDAI Desember 2025
Publisher : STMIK PPKIA Tarakanita Rahmawati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71302/jbidai.v8i2.80

Abstract

Poverty remains major social issue in Indonesia, so an analysis of its causal factors is necessary to assist the government in making informed decisions. This study aims to classify poverty levels using the C4.5 algorithm by utilizing a dataset containing various socio-economic indicators such as education level, unemployment, and per capita expenditure. The research stages began with data collection and cleaning, transformation, splitting the dataset into training and testing data, and building the classification model. The results show that the C4.5 algorithm is capable of classifying poverty levels effectively and producing clear decision tree patterns. Based on the generated model, the per capita expenditure variable was identified as the dominant factor most influencing poverty status in a region. This model is expected to serve as a basis for formulating more targeted policies to reduce poverty levels in Indonesia.
Co-Authors Basami Hutapea, Tio Kurniawan, Arga