Classification Analysis of Unilak Informatics Engineering Students Using Support Vector Machine (SVM), Iterative Dichotomiser 3 (ID3), Random Forest and K-Nearest Neighbors (KNN)

Abstract

This research is entitled “Classification Analysis of the Study Period of Informatics Engineering Study Program Students at Unilak with the Support Vector Machine (SVM), Iterative Dichotomiser 3 (ID3), Random Forest and K-Nearest Neighbors (KNN)" method. an attempt to understand whether there are factors that influence the length of a student's study period. Basically, the length of the study period is not a measure of a student's non-academic academic ability, but most people judge that students with a study period of more than 8 semesters or long are not good. Therefore, the researcher chose to classify the factors that affect the length of the student's study period at the Faculty of Computer Science, Lancang Kuning University. This study uses 4 (four) calculation methods. With the several methods used, the authors can compare the results of the four calculation methods so that they can determine which method is better calculated. The result of this research is a comparison between 4 (four) calculation methods in determining which method has good classification ability