ANALISIS KOMPETENSI SISWA PADA PELAJARAN PROGRAM KEAHLIAN MULTIMEDIA MENGGUNAKAN NAÏVE BAYES DAN DECISION TREE C4.5

Abstract

SMK is an educational institution that prepares human resources who are skilled and ready to be placed in the industrial world. One of its main activities is the implementation of street vendors and Expertise Competency Examinations which need to be carefully prepared by educational institutions. Determination of student competency scores can be obtained in 5 (five) productive subjects and can also be used as an attribute. In accordance with the infographic data published by BPS in 2019 that there are still 19% of SMK students who have not been absorbed in the industrial world, a research is needed by the SMK 1 Barunawati education unit as a form of school effort so that students who graduate can be absorbed in the industrial world. This research uses alumni data for class 2021 and 2022, namely 126 data sets which are divided into 2 parts, namely 101 as Training data and 25 as Testing data. The method used is the Naïve Bayes algorithm method and the C45 Decision Tree and the data processing application uses Rapid Miner application version 10 For Education, while the value data range has very good, good and sufficient information values ​​and has 2 classes, namely Very Competent and Competent. The results of data processing using the Rapid Miner application with the Naïve Bayes method obtained an accuracy value of 88% while using the Decision Tree C45 method an accuracy value of 72% is obtained so that it can be concluded that the use of the Naïve Bayes method is very good to use compared to the Decision Tree C45 method in this case study. The results of this research can be used as evaluation material for SMK 1 Barunawati in order to improve the quality of student competence.