Accuracy Analysis of Community Satisfaction in Population Administration Services Using the C4.5 Algorithm and Naïve Bayes Method: Accuracy Analysis of Community Satisfaction in Population Administration Services Using the C4.5 Algorithm and Naïve Bayes Method - Muhammad Andhika Maulana; Agung Triayudi; Ira Diana Sholihati (Institute of Computer Science (IOCS), 2020)
The Directorate General of Population and Civil Registration needs indicators for benchmarks in improving the quality of services for the community, one of which is conducting a survey of community satisfaction by using several attributes including requirements, mechanisms, completion times, product specifications, officer competencies, officer attitudes, reporting and advice as well as facilities and infrastructure where the satisfaction results can be classified using data mining. In this study, the authors tested two data mining classification methods, namely the C4.5 Algorithm method and the Naïve Bayes method using RapidMiner software. From the test method, the accuracy of 88.00% was obtained using the Naïve Bayes method and the C4.5 algorithm was obtained with an accuracy of 80.40%.