Penerapan Data Mining Pada Penerimaan Dosen Tetap Menggunakan Metode Naive Bayes Classifier dan C4.5 - Sadikin, Muhammad; Rosnelly, Rika; Roslina, Roslina; Gunawan, Teddy Surya; Wanayumini, Wanayumini (STMIK Budi Darma, 2020)
Recruitment is an important step in creating professional HR (Human Resources). The application of classification methods such as the Naïve Bayes method and C4.5 can be used in the classification of potential lecturers and can be accepted by the campus by calculating the equations for each criterion. The difficulty experienced is the ineffective use of the method to generate the required lecturer acceptance so that it is not in accordance with the applicant's expertise. One of the classification methods applied to data mining is the naïve Bayes method and C4.5. The purpose of this study is to determine the level of accuracy of the two methods used by using the Weka 3.8 tool based on the calculation of Correctly Classified Instance and Incorrectly Classified Instance. The accuracy results obtained with the naïve Bayes method are 83.7838% and the C4.5 method is 91.8919% from 37 training data. So the C4.5 method is a more appropriate method to use than naïve Bayes.