Open AccessPrediction of student learning outcomes using the Naive Bayesian Algorithm (Case Study of Tama Jagakarsa University)
Author(s) -
Arini Aha Pekuwali
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/823/1/012056
Subject(s) - computer science , student achievement , mathematics education , machine learning , bayesian probability , artificial intelligence , academic achievement , psychology
Assessment of student learning outcomes is the most important part in the learning process. Student achievement can be determined based on the achievement of final grades in certain subjects. Student final grades can be used to evaluate and predict student achievement in the future. This research was conducted to analyze the Naïve Bayesian Classifier (NBC) algorithm in predicting the final grades of students in the future based on student final grade data in the previous semester. This study is useful for students to improve their grades, according to their predicted weaknesses through this research (wake-up calling). The results of this study indicate that NBC successfully classifies data with an accuracy of 94.2446%.