Applying the Naive Bayes Algorithm to Predict the Student Final Grade
DOI:
https://doi.org/10.18196/eist.127Keywords:
Naive Bayes, E-Learning, Classification, Final GradeAbstract
The teaching and learning process of the Faculty of Engineering of Universitas Muhammadiyah Yogyakarta has used e-learning intensively. One of the benchmarks in determining students’ final grade is to take the values in e-learning. This study aims to predict students’ final grades by utilizing the data mining process and the Naive Bayes algorithm. This study provides students and lecturers information to enhance the teaching and learning process to improve students’ final grades and maintain satisfactory final grades until the lecture is complete. The research began with the literature study, data collection, data selection, data cleaning, data transformation and implementation with rapidminer and conclusion drawing. Based on the prediction of students’ final grades, one course obtained many unsatisfactory grades with an accuracy rate of 93.75%. Thus, the higher the accuracy value, the closer the predicted final value to the actual value.
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