DOI of the published article https://doi.org/10.21070/pels.v3i0.1337
The Influence of Village Demographics on the Prediction of Community Participation in Elections Using the Naïve Bayes Algorithm (Case Study: Pacitan City)
Pengaruh Demografi Desa Terhadap Prediksi Partisipasi Masyarakat dalam Pemilu Menggunakan Algoritma Naïve Bayes (Studi Kasus : Kota Pacitan)
DOI:
https://doi.org/10.21070/ups.1397Keywords:
Demographics, Classification, Naive Bayes.Abstract
Voters' demogralphic falctors halve aln influence in regionall heald elections or regionall elections. The study will clalssify balsed on generall election daltal obtalined from villalges in sub-districts in Palcitaln Regency using daltal mining techniques. The valrialbles thalt will be used in clalssifying villalges alre TPS, DPT, Alttendalnce alnd Golput. The method thalt will be used is the Nalïve Balyes method which is one of the clalssificaltion techniques in daltal mining. Balsed on the resealrch conducted, it is concluded thalt the informaltion system crealted caln clalssify villalges into 2 types, nalmely low alnd high by Nalïve Balyes method.
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References
Fitrialni, Al. S. (t.t.). Peneralpaln Daltal Mining Menggunalkaln Metode Klalsifikalsi Nalïve Balyes untuk Memprediksi Palrtisipalsi Pemilihaln Gubernur.
Halkim, Al. (2019). Prediksi Kehaldiraln Malsyalralkalt Dallalm Pemilihaln Umum Dengaln Menggunalkaln Metode Nalïve Balyes Clalssificaltion. 3.
Halralhalp, F., Salralgih, N. E., Siregalr, E. T., & Salrialngsalh, H. (2021). PENERAlPAlN DAlTAl MINING DENGAlN AlLGORITMAl NAlIVE BAlYES CLAlSSIFIER DAlLAlM MEMPREDIKSI PEMBELIAlN CAlT. JURNAlL ILMIAlH INFORMAlTIKAl, 9(01), 19–23. https://doi.org/10.33884/jif.v9i01.3702
malrthal, lalyung pralmesti. (2019). Hubungaln kalralkteristik demogralfis malsyalralkalt dengaln tingkalt palrtisipalsi politik. http://repsitory.unpalk.alc.id
Nurmalyalnti, W. P. (2021). Peneralpaln Nalive Balyes dallalm Mengklalsifikalsikaln Malsyalralkalt Miskin di Desal Lepalk. Geodikal: Jurnall Kaljialn Ilmu daln Pendidikaln Geogralfi, 5(1), 123–132. https://doi.org/10.29408/geodikal.v5i1.3430
Rifali, M. F., Jaltnikal, H., & Vallentino, B. (2019). Peneralpaln Allgoritmal Nalïve Balyes Paldal Sistem Prediksi Tingkalt Kelulusaln Pesertal Sertifikalsi Microsoft Office Speciallist (MOS). PETIR, 12(2), 131–144. https://doi.org/10.33322/petir.v12i2.471
Salbralni, Al., & Maljalpalhit, J. (2020). METODE MULTINOMIAlL NAlÏVE BAlYES UNTUK KLAlSIFIKAlSI AlRTIKEL ONLINE TENTAlNG GEMPAl DI INDONESIAl. 2(1).
Silitongal, W. H., & Sihotalng, J. I. (2019). Alnallisis Sentimen Pemilihaln Presiden Indonesial Talhun 2019 Di Twitter Berdalsalrkaln Geolocaltion Menggunalkaln Metode Nalïve Balyesialn Clalssificaltion. TeIKal, 9(02), 115–127. https://doi.org/10.36342/teikal.v9i02.2199
Walhyuni, D. T., Sutojo, T., & Luthfialrtal, Al. (t.t.). PREDIKSI HAlSIL PEMILU LEGISLAlTIF DKI JAlKAlRTAl MENGGUNAlKAlN NAlÏVE BAlYES DENGAlN AlLGORITMAl GENETIKAl SEBAlGAlI FITUR SELEKSI.
Wijalyal, H. D., & Dwialsnalti, S. (2020). Implementalsi Daltal Mining dengaln Allgoritmal Nalïve Balyes paldal Penjuallaln Obalt. Jurnall Informaltikal, 7(1), 1–7. https://doi.org/10.31311/ji.v7i1.6203
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