Model Analysis of the 2019 Election Participation Level Against Demographics in Pamekasan Regency Using the Naive Bayes Method

Maulana Habib Firmansyah (Department of Computer Science, Muhammadiyah University of Sidoarjo, Sidoarjo, Indonesia)
Arif Senja Fitrani (Department of Computer Science, Muhammadiyah University of Sidoarjo, Sidoarjo, Indonesia)
Azmuri Wahyu Azinar (Department of Computer Science, Muhammadiyah University of Sidoarjo, Sidoarjo, Indonesia)
Suhendro Busono (Department of Computer Science, Muhammadiyah University of Sidoarjo, Sidoarjo, Indonesia)

SAGA: Journal of Technology and Information Systems
Vol. 4 No. 2 (2026): May 2026

This study aims to analyze the level of election participation in 2019 in Pamekasan Regency based on demographic data using the Naive Bayes classification method. The data used consists of 189 instances and 208 predictor attributes obtained from the publication of the Central Statistics Agency (BPS). The analysis process involves the stages of preprocessing, feature selection, and model evaluation. The test results show a model accuracy of 66%, with the highest f1-score value in the high participation class. Further analysis also shows that most sub-districts and villages in Pamekasan have a high level of participation. In addition, a very strong correlation was found between demographic attributes that have the potential to be important predictors of voter involvement. These findings provide an initial overview to understand the factors that influence public participation in elections.