Analysis of C4.5 Algorithm Performance for Predicting Student Achievement Based on Socio-Economic Status, Motivation, Discipline, and Past Achievement - Purnama, Dimas Lucky Satya; Apsiswanto, Untoro (Journal of Computer Networks, Architecture and High Performance Computing, 2025)
Learning outcomes are changes that a person undergoes when learning. Learning outcomes can be in the form of changes in cognitive, affective, and psychomotor abilities depending on the learning objectives Student learning outcomes vary depending on each student's individual circumstances. Various factors such as family conditions, school environment, interests, motivation, and past achievements determine the success of learning outcomes. The problem occurring at SMK Negeri 4 Kota Metro is that the students come from various villages in the city. They mostly come from underprivileged families with low education levels. In addition, they are less motivated to study due to factors related to their family environment and the surrounding community. Most of the students at this school do not have good achievements in academic or non-academic fields.This research aims to predict student academic performance based on the socioeconomic status of parents, motivation, student discipline, and past achievements using data mining methods with the C.45 algorithm. For comparison, the research data was also analyzed with. The research approach used is quantitative. The subjects of this research are 606 students from the 10th grade of SMK Negeri 4 Kota Metro. The data collection techniques used were documentation and questionnaires. The research results show that the prediction analysis using decision tree has an accuracy of 98.02%, precision of 94.44%, recall of 77.27%, and AUC of 0.96.