SISTEM KLASIFIKASI KELULUSAN MAHASISWA DENGAN ALGORITMA RANDOM FOREST

Abstract

Some of the causes of students not graduating on time are the Cumulative GPA, which is below standard, the contracted courses do not pass, and the Number of leave taken. If left unchecked, this student's graduation time affects the accreditation value of the study program. For that, we need an application that can classify students who do not graduate on time from an early age so that supervisors and teaching lecturers can pay special attention to extra lessons, provide motivation, and can provide encouragement for students who are classified as not graduating on time so that the student can graduate on time. In this study, a student graduation classification application was made using the Random Forest algorithm. The attributes used to classify student graduation are Grade Point Average, Grade Point Average 1 to 4, Number of courses not passed, age, and gender, with 2 class outputs classified as punctual and late. This application development uses Waterfall and Unified Modeling Language (UML) as modeling tools. Testing of student graduation classification applications using the Random Forest algorithm, which is carried out using 60% training data and 40% test data. The test was performed five times, and the highest accuracy obtained was 90.00% using 50 trees.