APPLICATION OF THE K-MEANS AND DECISION TREE ALGORITHMS IN DETERMINING STUDENT ACHIEVEMENT
Abstract
Various factors influence student achievement, both internal and external; this makes it difficult for some teachers to detect every student in class. This research aims to determine student achievement in class among students at the SDS Kartika X-6 school. Data comes from SDS Kartika X-6, an elementary school owned by the Indonesian Army. By knowing the factors that influence the determinants of student learning achievement, steps can be taken to improve student learning achievement at SDS Kartika x-6. The methods used in this research are the K-Means algorithm and Decision Tree. This method will be chosen to determine student learning achievement. The process begins by determining clusters using the K-Means algorithm; then a classification process is carried out using a Decision Tree. The number of datasets in this research is 28, and the criteria are gender, mathematics grades, English, natural sciences, religion, class performance, and school achievement. The implementation results show that academic grades, class achievements, and school achievements play a role in determining student achievement for SDS Kartika X-6 students. Meanwhile, 3 clusters were formed: Fairly Good, Good, and Very Good. In the testing stage using the Decision Tree method, prediction accuracy was 71%, with an error of 29.
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DOI: https://doi.org/10.33387/jiko.v7i1.7580
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