Comparative Analysis Accuracy ID3 Algorithm and C4.5 Algorithm in Selection of Candidates Basic Physics Laboratory Assistant

Abstract

Basic Physics Laboratory is one of the supporting laboratories at Gunadarma University. Each practical activity in the laboratory is supervised by respective assistants. Therefore, a support system is needed as a basis for decision-making in determining assistant candidates. This decision-making process is processed using data mining techniques, specifically classification algorithms. The criteria or attributes used in the decision-making process include written test scores, practical test scores, presentation scores, equipment usage abilities, and interviews. The classification algorithms used in this research are ID3 and C4.5 algorithms. The tools used to implement these algorithms are RapidMiner Studio 9.10. These algorithms will generate decision trees that can be used as decision support. The aim of this research is to conduct an accuracy comparison analysis for the ID3 and C4.5 algorithms. The highest accuracy obtained will be used as a reference for determining whether assistant candidates are accepted or not. The accuracy results show that the C4.5 algorithm has the highest accuracy, precision, and recall compared to the ID3 algorithm. The determination of the highest value is done using the k-fold cross-validation model for values 2, 4, 6, 8, and 10. The C4.5 algorithm has the highest accuracy of 96.67% at k-fold value = 2.