PEMBENTUKAN MODEL KLASIFIKASI DATA LAMA STUDI MAHASISWA STMIK INDONESIA MENGGUNAKAN DECISION TREE DENGAN ALGORITMA NBTREE

Redaksi Tim Jurnal

Kilat
Vol 6 No 2 (2017): KILAT

One of the assessment criteria for the accreditation of the study program is the assessment of the duration of the study of students who graduated on time. not a few students who pursue the study period exceeds the established standard of graduation. So it is important for the study program to know which students have the possibility of passing is not timely. For that it is necessary to predict the length of student study. One way to predict the length of a student's study is to build a classification model. This study aims to build a long prediction model of student study using Decision Tree with NBTree algorithm. The data used are academic value data and student academic leave data. The result obtained is a classification model of Naïve Bayes Decision Tree with 73.45% accuracy.