Analysis of Student Dropout at State Senior High School 6 Padangsidimpuan City Using the C5.0 Decision Tree Algorithm

Abstrak

The issue of student dropouts in Indonesia, including at SMA Negeri 6 Padangsidimpuan City, poses a significant challenge in the field of education. This phenomenon hampers the achievement of compulsory education programs and impacts the quality of human resources. The dropout rate at SMA Negeri 6 Kota Padangsidimpuan reached 19.08% in the 2023/2024 academic year, highlighting the urgency of this problem. Factors such as economic conditions, geographical constraints, and individual motivation are the primary contributors to this issue. This study aims to analyze the factors contributing to student dropouts using the C5.0 decision tree algorithm method. The research data was collected through interviews, observations, and school archives, then processed using RapidMiner software. The research process included data preprocessing, classification model development, and model evaluation using a confusion matrix. The results showed that the C5.0 decision tree algorithm could identify significant relationships among these variables, achieving an accuracy rate of 87%. In conclusion, the C5.0 decision tree algorithm is effective in analyzing the factors causing dropouts and can serve as a basis for formulating more targeted prevention strategies.