PERANCANGAN APLIKASI PREDIKSI MASA STUDI MAHASISWA DENGAN METODE NAÏVE BAYES DAN C4.5 - Charles Yuliansen; Bagus Mulyawan; Novario Jaya Perdana (Fakultas Teknologi Informasi Universitas Tarumanagara, 2019)
In college studies each study period uses a semester system where each semester of study period will obtain a Grade Point Average (GPA) in which the GPA shows the value obtained during the study period in that semester. With the right calculation the GPA can be used as a long time determinant of a student's study period. This prediction application is made using the classification method. The data used is obtained legally from the faculty and is used to carry out the training process and test applications that have been made. For the development method use the test structure method with several tools and workmanship techniques such as flowcharts, context diagrams, and relationships between tables. The programming language used in making applications is PHP, Python, the database used is MySQL. The training and testing methods used in making the application are Naïve Bayes and C4.5. The results of system testing show that using 237 student data obtained that the C4.5 method is always superior compared to the Naïve Bayes method. Addition of sex variables did not change the accuracy significantly.