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All Journal Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK)
Agatha, Veronica Nadya
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Computer Science & IT Electrical & Electronics Engineering

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Perbandingan Metode Klasifikasi Naive Bayes dan K-Nearest Neighbor pada Data Status Pembayaran Pajak Pertambahan Nilai di Kantor Pelayanan Pajak Pratama Surakarta Agatha, Veronica Nadya
Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) 2024: SNESTIK IV
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/p.snestik.2024.5880

Abstract

Value Added Tax (VAT) is a tax added to a transaction. VAT also serves as a source of state revenue to support national development. This research was motivated by the city of Surakarta which had obtained the title as the second tax-abiding city in Central Java so that it was necessary to review the suitability between the implementation, deposit, and reporting of VAT with applicable regulations. In this study, a comparison of the naïve Bayes and K-Nearest Neighbor methods was carried out on the classification of VAT tax payment status in Surakarta in 2023. This study uses tax payment compliance data based on data from the Surakarta Pratama Tax Service Office with a Tax Payment Status classification label. To evaluate accurate results, accuracy level measurements are carried out using Apparent Error Rate (APER). The results of this study showed that the Bayes naïve method had better classification performance with an APER value of 8.31% while the K-NN method was 13.07%.
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