Predicting Online Learning Student Results Using Machine Learning

Due to the pandemic which causes online learning, students are forced to adapt to a new system that they need help for. The aim of the study is to predict the student's GPS in an early stage so that the teacher can get the early warning for several students to help them further in their studies. To get the outcome of the student prediction, we can use five of the data-mining techniques which are Artificial Neural Network (ANN), Decision Tree (DT), Support Vector Machine (SVM), Naive Bayes (NB), and Logistic Regression (LR). The study was conducted with a dataset of 101 records of students enrolled in Bina Nusantara University. The study confirms that the usage of the method to do the predicting will take on effect on the prediction result. In this case, the usage of NB will be the most suited method for our data models followed by ANN and LR.