The inter-city public transport competition between provinces encourages otobus companies to require maximum service quality for customer satisfaction. PO. XYZ is one of the otobus companies that is interested in the people of Central Java and East Java in general to the capital city of Jakarta and surrounding areas, but the level of customer satisfaction for the services provided has not been well predicted. Therefore we need an analysis of the level of satisfaction with the services provided. From these considerations, the authors use the Naïve Bayes method to analyze customer satisfaction with customer satisfaction PO. XYZ. The test uses Rapidminer 9.1, and is implemented into a web-based system to make it easier to determine the level of customer satisfaction. Based on the results of the analysis obtained in the research conducted applying the Naïve Bayes method for prediction of customer satisfaction with services from PO. XYZ It can be concluded that, the Naïve Bayes Method is used by using training data to obtain the probability of each criterion for different classes, then the values of these criteria can be optimized to predict new customer satisfaction, namely by testing the data. From the results of tests that have been done, get a high level of accuracy that is equal to 94.00%. Keywords: Customer Satisfaction, Data Mining, Naïve Bayes, Data Training, Data Testing, Rapidminer.
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