ABSTRACT
Machine learning algorithms are used for various purposes to predict, classify, or forecast by training the algorithms with the specific dataset. SVR and multiple linear regression can take numerous features to forecast or predict scores through the train-test-split. The education sector has been changed rapidly due to the pandemic of COVID-19 where online classes are being a module worldwide. However, junior schools or colleges stubbed into a position where student performance measurement is a hindrance due to the lack of taking physical examinations. During the COVID-19, student performance can be acquired using the previous achievement of individual students where multiple conditions can be applied. The aim of this paper is to train and test the conditional dataset of student's results through SVR and Multiple Linear Regression to predict and justify the results in accordance with using the proposed model in the future. As conditions have been applied to the individual subjects when calculating new results based on the previous achievement of student’s performance so that each subject’s score has been trained and tested individually through the machine learning algorithms. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.