ANALISIS HUBUNGAN MATA KULIAH KOMPUTASI DASAR DENGAN IPK MAHASISWA TEKNIK INFORMATIKA MENGGUNAKAN SUPPORT VECTOR REGRESSION - Perdana, Novario Jaya; Ferdinand, Kelvin; Gozali, Carisha Puspa; Herwindiati, Dyah Erny (ISTEK WIDURI, 2025)
Student academic performance serves as a key indicator in higher education assessment. For students in Informatics Engineering, foundational computing skills are critical to their academic progression, and these are primarily acquired through first-semester courses. This study proposes a predictive model for Cumulative Grade Point Average (GPA) using the Support Vector Regression (SVR) method with a Radial Basis Function (RBF) kernel. The courses