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All Journal The IJICS (International Journal of Informatics and Computer Science)
Fajrillah Fajrillah
Sekolah Tinggi Ilmu Ekonomi IBBI
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Implementation of Data Mining Using Naïve Bayes Classification Method To Predict Participation of Governor And Vocational Governor Selection In Jemirahan Village, Jabon District Arif Senja Fitrani; Fajrillah Fajrillah; Wirda Novarika
The IJICS (International Journal of Informatics and Computer Science) Vol 3, No 2 (2019): September 2019
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (447.622 KB) | DOI: 10.30865/ijics.v3i2.1391

Abstract

General Election (ELECTION) is an important political event to determine a leader in a democratic country. The General Election (ELECTION) in East Java which was held on 27 June 2018 yesterday was the election of the Governor and Deputy Governor for the 2019-2024 period. There are two pairs of candidates for Governor and Deputy Governor. Through the General Election (ELECTION) then all parties can be accommodated what they want and aspire to so that a better life can be realized. The community is the determining component of the success or failure of an Election. Therefore, in this study the researcher wanted to examine how the electoral participation in Jemirahan Village, Jabon District by using the classification method, the Naïve Bayes algorithm. To predict the participation of the General Election (PEMILU) in Jemirahan Village, Jabon District, it can be done using the Naïve Bayes Algorithm with 6 predefined variables. The results of the prediction of election participation from the dataset taken were 300 data divided by 2, as many as 65% of 195 training data and 35% of 105 data testing.
Co-Authors Arif Senja Fitrani Wirda Novarika