Student Performance Using Antlion Optimization Algorithm and ANN Regression

The prediction of student performance is one of the most important topics in educational data mining. The use of artificial neural networks in a learning environment is considered to be an effective way of predicting student performance. In this paper, the data set was collected from colleges and universities. The data collection has 437 entries in total. To select the best features, we are using the ant lion optimization algorithm and predict the performance of students using an Artificial Neural Network. The result of the model is shown by using RMSE (1.10), MAE (0.54), and MSE (1.10). The artificial neural network developed by the study predicts with an accuracy of 98%.