ANALISIS POLA KEHADIRAN MAHASISWA MENGGUNAKANALGORITMA DECISION TREE - Mu’tashim Billah Rahman; Zaehol Fatah (CV. Denasya Smart Publisher, 2025)
Student attendance in lectures plays a crucial role in academic achievement and the quality of learning. The Decision Tree algorithm is used to analyze student attendance patterns with a dataset containing 6,607 entries from Kaggle, comprising 20 related attributes. Using RapidMiner, the analysis process includes data splitting, model building, and performance evaluation. The model achieved 49.96% accuracy, with the best performance in the