Model Analysis of the 2019 Election Participation Level Against Demographics in Pamekasan Regency Using the Naive Bayes Method
Abstract
This study aims to analyze the level of participation in the 2019 elections in Pamekasan Regency based on demographic data using the Naive Bayes classification method. The data used consisted of 189 instances and 208 predictor attributes obtained from the Central Statistics Agency (BPS) publication. The analysis process involved preprocessing, feature selection, and model evaluation stages. The test results showed a model accuracy of 66%, with the highest f1-score value in the high participation class. Further analysis also shows that most subdistricts and villages in Pamekasan have high participation rates. In addition, a very strong correlation was found between demographic attributes that have the potential to be important predictors of voter engagement. These findings provide an initial overview to understand the factors that influence community participation in elections.
Fields of Study & Subjects
Indonesian Election Politics and Participation
Data Mining and Machine Learning Applications
Economic Growth and Fiscal Policies
Publication details
- Journal / source
- SAGA Journal of Technology and Information System
- Volume
- 3
- Issue
- 1
- Pages
- 141–148
- Publication date
- 23 April 2026