Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : EDUMATIC: Jurnal Pendidikan Informatika

Penerapan Algoritma Support Vector Machine untuk Memprediksi Tingkat Partisipasi Pemilu terhadap Kualitas Pendidikan Anggraeni, Anifah Warda; Fitrani, Arif Senja; Eviyanti, Ade
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.24838

Abstract

Elections are a democratic means of choosing leaders. Public participation in elections is important for a healthy democracy. The quality of education influences public participation in elections. Therefore, the government needs to improve the quality of education in the Pasuruan Regency area. This research aims to predict the level of participation in elections on the quality of education in Pasuruan Regency. This research uses the Education sector dataset obtained from BPS data for Pasuruan Regency in 2022 and the level of election participation obtained from the recapitulation of the 2019 election results. Data analysis was carried out in an experimental stage to determine the variables to be predicted (target variables) and the variables used to predict it (predictor variable) using the Support Vector Machine (SVM) algorithm with three kernels, namely linear, rbf, and polynomial. The findings show an accuracy of 88.4% for the linear kernel, 88.5% for the rbf kernel, and 88.5% for the polynomial kernel. The quality of education can influence the level of election participation. This is because high quality education can increase public awareness of the importance of participating in elections.