ANALISIS FAKTOR PERFORMA AKADEMIK MATEMATIKA SISWA DENGAN PERBANDINGAN ALGORITMA MACHINE LEARNING - Zuhriya, Tasbi Khatuz; Daniati, Erna (Prosiding Seminar Nasional Teknologi dan Sistem Informasi, 2025)
Mathematics is one of the sciences that is often used by humans in everyday life, because with the existence of mathematics, it can help humans to form a mindset of human reasoning abilities. Even so, not all students like mathematics, but for some students who consider mathematics to be a fun science, this can be influenced by several factors. In this study, an analysis will be conducted on the factors of students' mathematical academic performance which include parental educational background, gender, economic status, tutoring / additional courses, and reading and writing skills by using a comparison of machine learning algorithm models such as Linear Regression, Random Forest, and Gradient Boosting. Of the three algorithm models, Linear Regression with an RMSE value of 5.37, MAE = 4.23, and the highest R2 value with a value of 0.88. And the conclusion of this study is that the factors that most influence students' mathematical academic performance are gender, parental educational background, and reading and writing skills.