| dc.contributor.author | Rahmaulidyah, Fatihah Noor | |
| dc.contributor.author | Hayati, Memi Nor | |
| dc.contributor.author | Goejantoro, Rito | |
| dc.date.accessioned | 2022-01-19T12:40:30Z | |
| dc.date.available | 2022-01-19T12:40:30Z | |
| dc.date.issued | 2021-11 | |
| dc.identifier.issn | 2798-3455 | |
| dc.identifier.uri | http://repository.unmul.ac.id/handle/123456789/15907 | |
| dc.description.abstract | Classification is a systematic grouping of objects into certain groups based on the same characteristics. The
classification method used in this research are naive Bayes and K-Nearest Neighbor which has a relatively high
degree of accuracy. This research aims to compare the level of classification accuracy on the status data of
value-added tax (VAT) payment. The data used is data on corporate taxpayers at Samarinda Ulu Tax Office in
2018 with the status of VAT payment being compliant or non-compliant and used 3 independent variables are
income, type of business entity and tax reported status. Measurement of accuracy using APER in the Naive
Bayes method is 17.07% and in K-Nearest Neighbor method is 19,51%. The comparison results of accuracy
measurements between the two methods show that the naive Bayes method has a higher level of accuracy than
the K-Nearest Neighbor method. | en_US |
| dc.language.iso | other | en_US |
| dc.publisher | Jurusan Matematika FMIPA Universitas Mulawarman | en_US |
| dc.relation.ispartofseries | Vol 12 No 2 (2021): Jurnal Eksponensial;no. 2 | |
| dc.subject | classification, naive Bayes, K-Nearest Neighbor, tax. | en_US |
| dc.title | Perbandingan Metode Klasifikasi Naive Bayes dan K-Nearest Neighbor pada Data Status Pembayaran Pajak Pertambahan Nilai di Kantor Pelayanan Pajak Pratama Samarinda Ulu | en_US |
| dc.title.alternative | The Comparison of The Naive Bayes and K-Nearest Neighbor Classification Methods on The Data Payment Status of Value Added Tax at The Samarinda Ulu Pratama Tax Service Office | en_US |
| dc.type | Article | en_US |
