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Azmi, Khoiratul
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Computer Science & IT

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Journal : Journal of Computer Science and Informatics Engineering

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Penerapan Data Mining Menggunakan Clasifcasion Untuk Potensi Biaya Pajak Azmi, Khoiratul; Evioni, Aninda
Journal of Computer Science and Informatics Engineering Vol 4 No 1 (2025): Januari
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v4i1.990

Abstract

Increasing tax revenue is one of the government's main focuses in development efforts. One way to maximize tax revenue is to identify potential tax costs that have not been ideally explored. In this study, information mining techniques are applied with the classification method to predict and identify taxpayers who have the potential for high tax costs. By using historical taxpayer information, the classification method is able to group taxpayer information into certain categories that are useful for further analysis. The results of this study are expected to provide information-based recommendations to tax authorities in order to improve the efficiency of tax collection.
Co-Authors Evioni, Aninda