Random forest algorithm for algorithm for prediction of high school science students acceptance snmptn based on students assesment report

Abstract

National Selection for State University (SNMPTN) is one of the selection lines for admission of new students in Indonesia to enter State Universities by invitation. Report card grades are one component of the assessment of admission of new students to enter state universities on this pathway. The difference in standards between universities in determining the admission of SNMPTN applicants, causing the need to predict based on several related factors. This research uses data mining techniques with Random forest algorithm. From the results of research that has been done, it was found that the Random Forest algorithm can be used to predict students who are accepted at SNMPTN based on report card grades, obtained from the results of the classification process with the student report card report survey dataset received by SNMPTN, This is indicated by the accuracy, precision, and recall values of 93%. Optimization of the random forest algorithm using the oversampling technique with the SMOTE method can improve the classifier's performance due to the imbalanced class problem.