Application of Data Mining Using Classification Technique Methods to See Potential Vehicle Taxpayer Compliance
DOI:
https://doi.org/10.55537/cosie.v3i1.710Keywords:
Kata Kunci : PKB, Data Mining, Naïve Bayes, RapidminerAbstract
The aim of this research is to examine motor vehicle taxpayer compliance, with a focus on South
Medan Samsat and Medan City PEPENDA UPTD. The main source of funding for development
and state services that can be enjoyed by the whole community is taxes, which contribute more
than 70% of state income. The Regional Revenue Agency (Bapenda) manages Motor Vehicle Tax
(PKB) which is classified as a regional tax and is handled by the Joint Office for One-Stop
Integrated Administrative Systems (SAMSAT). We can identify compliant and non-compliant
taxpayers by using a sample of motor vehicle taxpayer data from the South Medan Samsat,
precisely in May 2023. In this research, data mining is applied in conjunction with the
Classification Technique using the Naïve Bayes algorithm to identify, with an accuracy of
70.91%, among 110 taxpayers there are those who have the potential to comply (prior probability
value: 0.564) and those who have the potential to not comply (prior probability value: 0.436).
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