APLIKASI DATA MINING UNTUK MENENTUKAN LULUSAN MAHASISWA TEPAT WAKTU - wendi, Al; Mandopa, Andi; Budiarti, Lela (Journal of Advanced Research in Informatics, 2024)
Untimely graduation rates have become an important problem in the world of education that can affect the quality of education and cause additional costs for students and educational institutions. This research aims to build a prediction model to predict the acceptance of prospective new students at Graha Nusantara University, especially in the Computer Science study program. In achieving the graduation process, students must meet the requirements including GPA, Gender, Region of Origin, School of Origin. The research results show that the prediction model built using the rule association algorithm in this study had good accuracy, namely 38.3 percent. This research examines the application of data mining methods with the association rule algorithm, to predict student graduation on time at Graha Nusantara University. This research produces findings that this method makes it easier to determine student graduation patterns. Association rule is a data mining technique that finds patterns, dependencies, and connections between items in data. These algorithms can be used to explain patterns in seemingly independent data, such as relational databases and transactional databases.