Model Prediksi Untuk Menentukan Predikat Kelulusan Siswa Menggunakan Algoritma Naïve Bayes Dan Mlp: Studi Kasus Smk Buddhi Tangerang - Santa Margita (Fakultas Sains dan Teknologi-Universitas Buddhi Dharma, 2022)
Students of Vocational High School received the title of graduation after finished their studies. Whether graduating students capable or not to get high predicate was influenced by several factors. The factors that could affect the values are the averages of report, National Examination (UN), skill, Vocational Competency Exam (UKK), and attitude in knowing the pattern of these variables. The previous research showed that Naïve Bayes algorithm has high accuracy value. Accuracy value obtained prove that the Naïve Bayes has good accuracy percentage. Thus this algorithm can predict graduating students of SMK Buddhi Tangerang in terms of determining the predicate obtained. This research used the Naïve Bayes algorithm and MLP in knowing the pattern of these variables. Testing was done by Confusion Matrix. The percentage results of accuracy proved that the Naïve Bayes was 92%, while MLP 90%. Thus Naïve Bayes algorithm has higher accuracy value than MLP. Naïve Bayes algorithm could predict the predicate which was obtained by graduating students of Buddhi Dharma Vocational High School Tangerang. Keywords : Naïve Bayes, MLP, vocational students, data mining, vocational