Random forest algorithm for algorithm for prediction of high school science students acceptance snmptn based on students assesment report - U Pujianto; A R Taufani; J A Aziz (Universitas Ahmad Dahlan, 2021)
National Selection for State University (SNMPTN) is one of the selectionlines for admission of new students in Indonesia to enter State Universities byinvitation. Report card grades are one component of the assessment ofadmission of new students to enter state universities on this pathway. Thedifference in standards between universities in determining the admission ofSNMPTN applicants, causing the need to predict based on several relatedfactors. This research uses data mining techniques with Random forestalgorithm. From the results of research that has been done, it was found thatthe Random Forest algorithm can be used to predict students who are acceptedat SNMPTN based on report card grades, obtained from the results of theclassification process with the student report card report survey datasetreceived by SNMPTN, This is indicated by the accuracy, precision, and recallvalues of 93%. Optimization of the random forest algorithm using theoversampling technique with the SMOTE method can improve the classifier'sperformance due to the imbalanced class problem.