Implementation of Naive Bayes Classifier Algorithm to Evaluation in Utilizing Online Hotel Tax Reporting Application

Abstract

The current implementation of tax reporting regional Pasuruan hotels have used online (Web-based), with the aim of reporting systems can run effectively and efficiently in receiving the financial statements especially from taxpayer property. Pasuruan as one small town quite rapidly in East Java, have implemented role models online tax filing system starting in 2015, with the amount of 6 hotels, there are several classes of hotels ranging from the budget class up to class three stars. After the application of the system running for 18 months (2015-2016), from existing data, conducted research on the analysis of the level of compliance of taxpayers reporting incomes in a hotel. On the research was designed and built a system to evaluate the level of compliance with the performance from the taxpayer (WP) in the 2nd year (2016) and are classified in categories (1) the taxpayer (WP) very obedient (ST), (2) the taxpayer (WP) is quite obedient (CT), (3) Taxpayers (WP) less obedient (KT). Input data will be processed using the technique of data mining algorithms Naive Bayes Classifier (NBC) to form the table of probability as a basis for the process of classification levels of taxpayer compliance. Based on the results of the measurement, the test results show with an accuracy of 50% i.e. 3 taxpayers is the very obedient (ST) to pay taxes. Then from the classification, the study could be made of recommendation solutions to guide the taxpayer in reporting revenues well and true.