SISTEM REKOMENDASI PENERIMAAN MAHASISWA BARU MENGGUNAKAN NAIVE BAYES CLASSIFIER DI INSTITUT PENDIDIKAN INDONESIA - Andri Suryadi; Erwin harahap (Universitas Islam Lamongan, 2018)
The quality of a university in creating qualified graduates is determined by the prospective students who enter the college. One of the things that can determine the quality is how the selection process of candidates for good student acceptance. However, the selection process of admissions in every college of course is different. Often the input of prospective students who enter the university is not in accordance with the expected so that the impact of graduate results. Therefore it is necessary for a system that can support the decision in the selection of new student candidates in order to get a good student input. This research builds a Recommendation System that will assist in the selection process of universities for the selection team of new student candidates. This recommendation system uses the naïve Bayes classifier method where the test scores of incoming selection of students who have been accepted will be used as training data and then classified based on the value of ipk that has been obtained. The value of the ipk will be a benchmark for the formation of classes - classes that are recommendations to the selection team. The classes that are formed are classes whose ipk value is at the accepted point and the class whose ipk value is not accepted. Then given a new student data, if the prospective student enters the safe class then it will be recommended to be accepted but otherwise it will be recommended to be rejected