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All Journal Indonesian Journal of Cultural and Community Development
Yuwanto, Mahmud Adi
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Humanities Languange, Linguistic, Communication & Media

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Journal : Indonesian Journal of Cultural and Community Development

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Decision Tree Analysis for Predicting Voter Participation Using IDM Data: Analisis Pohon Keputusan untuk Memprediksi Partisipasi Pemilih Menggunakan Data IDM Yuwanto, Mahmud Adi; Fitrani, Arif Senja; Dijaya, Rohman; Indahyanti, Uce
Indonesian Journal of Cultural and Community Development Vol. 16 No. 2 (2025): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijccd.v16i2.1255

Abstract

General Background: Voter participation serves as a core indicator of democratic quality and civic awareness. Specific Background: In East Java’s Mataraman region, significant disparities in electoral participation highlight socioeconomic influences measurable through the Village Development Index (IDM). Knowledge Gap: No prior research integrates IDM-based indicators with machine learning methods for voter behavior prediction. Aims: This study develops a classification model using C4.5, Naïve Bayes, and SVM algorithms to predict voter participation based on IDM attributes. Results: The Decision Tree C4.5 algorithm achieved the highest accuracy (80.87%) and F1-score (0.88) compared to Naïve Bayes and SVM, identifying education and healthcare access as primary determinants of high participation. Novelty: The integration of IDM and C4.5 classification introduces a novel framework for data-driven political participation analysis. Implications: The model can assist policymakers and electoral bodies in targeting civic engagement initiatives within underrepresented regions. Highlights: C4.5 algorithm effectively predicts voter engagement. Education and health access influence participation. Data-driven policy enhances democratic quality.
Co-Authors Arif Senja Fitrani Rohman Dijaya Uce Indahyanti