PREDIKSI KINERJA MAHASISWA DALAM PERKULIAHAN DARING BERBASIS E-LEARNING MENGGUNAKAN METODE LOGISTIC REGRESSION

Abstract

There are many problems that occur in the online learning process, one of which is the difficulty of students in understanding the material well. Various efforts have been declared by lecturers to support online learning, starting from direct material explanations through OpenLearning, Zoom, and Google Meet media. To find out whether the student's performance in this online lecture is good or not. Prediction of student performance in online lectures is used as one of the supports for evaluation decisions at the University of Muhammadiyah, East Kalimantan. The purpose of this study is to determine indicators, implement and evaluate the performance of the Logistic Regression algorithm using the confusion matrix to see student performance in online lectures. The number of data used in this study was 2663 data on odd semester citizenship courses in 2020/2021 and 2021/2022. . The results of the Logistic Regression algorithm using 80% training data sharing and 20% testing data obtained an accuracy value of 91.66%.