PENERAPAN ALGORITMA NAÏVE BAYES UNTUK PREDIKSI PENERIMAAN SISWA BARU DI SMK AL-AMIEN WONOREJO - ; Saful Rizal; Moch. Luthfi (Program Studi Teknik Informatika, Fakultas Teknik, Universitas Yudharta Pasuruan)
One aspect of the first high school quality indicator is the level of acceptance of students in senior high schools or public vocational schools. Some junior high school students' data were analyzed to determine the level of acceptance of students in senior high schools or state vocational high schools. The process of analyzing student data using data mining techniques. The purpose of this research is to know the application of naïve bayes classification on the average value of report cards and the value of national examination on the acceptance level of students in high school or public vocational school using the result of classification model that formed. In this study the data used is the new student data force 2016 Vocational High School AL-AMIEN Wonorejo. Data mining process is assisted by WEKA software using naïve bayes classification and 10-fold cross validation. Furthermore the naïve bayes classification model is used to process prediction data. The results of the testing of the Naïve Bayes algorithm in predicting the acceptance of new students at the AL-AMIEN Wonorejo Vocational High School in 196 data of the students tested in this study, showed that the Naïve Bayes algorithm has an accuracy rate of 86.22%.