APPLICATION OF THE NAIVE BAYES METHOD FOR DETERMINING THE ELIGIBILITY OF TOLL FARE REFUND REPORTS FOR MISCLASSIFIED VEHICLES
Keywords:
Naive Bayes, Reporting Data, Vehicle Fares.Abstract
Vehicle misclassification at toll gates results in fare discrepancies for toll road users. The verification of fare refund reports, which is currently performed manually, is time-consuming and prone to human error. To address this problem, this study aims to design and implement a system based on the Naive Bayes method that automatically classifies and verifies the eligibility of vehicle fare reports. The Naive Bayes method was selected for its ability to process heterogeneous data and to produce accurate probability-based classifications. The system utilizes evidence such as payment receipts, e-toll transaction histories, and vehicle data to determine report eligibility. The collected data were analyzed to identify relevant patterns, enabling the system to generate appropriate decisions within a short time. The results indicate that the application of the Naive Bayes method improves the efficiency and accuracy of the report verification process. The developed system significantly reduces verification time and produces more consistent results than the manual process. The implementation of this system is expected to improve the quality of service for toll road users, minimize fare calculation errors, and increase customer satisfaction.
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