Classification of Factors Causing the Decline in Student Learning Achievement in The Post-Pandemic Period Using the C4.5 Algorithm (Case Study: STMIK Kaputama)

Abstract

The COVID-19 pandemic that has hit Indonesia since 2020 has brought significant changes to various aspects of life, including the learning system in universities. Universities, which originally implemented face-to-face learning processes, were forced to adapt to online learning. However, this change causes various obstacles, especially for students who experience learning loss, namely a decrease in interest and motivation to learn which has an impact on academic achievement. This research aims to classify the factors that cause the decline in student learning achievement in the post-pandemic period at STMIK Kaputama using the C4.5 algorithm. Using data from STMIK Kaputama students as a sample, this research analyzes various factors such as access to technology, involvement in online learning, participation in face-to-face learning, social support, learning motivation, economic conditions, family, college, and academic stress levels. It is hoped that the results of this research will provide a deeper understanding of the dominant factors that cause a decline in learning achievement, as well as become a reference for educational institutions in developing strategies to overcome the negative impacts of online learning during the pandemic Keywords: C4.5 Algorithm, Decrease in Achievement, Data Classification