PREDIKSI KELULUSAN MAHASISWA MENGGUNAKAN ALGORITMA DECISION TREE C4.5 DENGAN TEKNIK PRUNING

Abstract

The system created are used to predict the length of study period required for students to complete their studies based on their grades. The system created also have online consultation features that students use with their academic lecturer for academic consultations. To find the model tree with good accuracy, the system will use k-fold cross validation in the process of making model tree. Testing prediction system using students data from 2008 to 2012 who have completed their studies. The value data used is all mandatory courses  in the Faculty of Information Technology except for thesis courses. Based on the tests performed, the system can already run and used in accordance with the design made. The test is to compare the accuracy of the selected tree model from different k values in the k-fold cross validation process. The results obtained show that if the value of k the greater, then the accuracy obtained better.