Jordi Lasmana Putra
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ANALISIS KINERJA ALGORITMA C4.5 DAN NAÏVE BAYES DALAM MEMPREDIKSI KEBERHASILAN SEKOLAH MENGHADAPI UN Siti Fauziah; Yeni Angraini; Siti Fauziah; Jordi Lasmana Putra
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 5 No 2 (2020): JITK Issue February 2020
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1174.77 KB) | DOI: 10.33480/jitk.v5i2.1233

Abstract

The national exam (UN) is one of the determinants of student graduation, both elementary school, junior high school and even high school. There are many businesses that are carried out by schools to prepare their students to face national examinations. In fact almost all schools provide material deepening to their students for subjects tested at the national examination. Therefore, this study was conducted to determine the level of success of the school in preparing students in facing national examinations. The method used is a decision tree with C4.5 algorithm and naïve Bayes algorithm. From the results of the study, the results of the accuracy of the naïve bayes algorithm were as big as 95,50% , while accuracy using the c4.5 algorithm is equal to 78,50%. Then it can be concluded that the predictions generated from the naïve bayes algorithm are better compared to the c4.5 algorithm .