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Bowval Valentino
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Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Penerapan Algoritma Naïve Bayes Pada Sistem Prediksi Tingkat Kelulusan Peserta Sertifikasi Microsoft Office Specialist (MOS) Mochamad Farid Rifai; Hendra Jatnika; Bowval Valentino
PETIR Vol 12 No 2 (2019): PETIR (Jurnal Pengkajian Dan Penerapan Teknik Informatika)
Publisher : Sekolah Tinggi Teknik - PLN

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (681.614 KB) | DOI: 10.33322/petir.v12i2.471

Abstract

This research discusses prediction pass rates the certification microsoft office specialist 2013 version (word and excel) aimed to provide information concerning to pass rates and certification give alternative solutions to determine the program certificationi appropriate to chosen before test certification. Naive bayes used for the classification certification graduation where participants know what information pass and did not finish. Naive bayes is a classification with the probability and statistics to predict opportunities in the future based on the Provided before. In this study, system development CRISP-DM to use of the become more ordered and testing done with the BlackBox to test each function is on the application built. From the study, produce values probability of 0.001042 the accuracy of 99 %. These results, proving that naïve bayes method can be used to assist in a prediction graduation rates participants (word and excel), because it produces quite high accuracy. So participants were able to determine the certification program proper chosen before test certification.
Co-Authors Hendra Jatnika Mochamad Farid Rifai