Fortech : Journal of Information Technology
Vol 8 No 2 (2024): Fortech (Journal Of Information Technology)

ANALISIS PREDIKSI KELULUSAN MAHASISWAFILKOM UNIVERSITAS NURDIN HAMZAH DENGAN METODE NAIVE BAYES

Limia Budiarti, Rike (Unknown)
Kahar, Novhirtamely (Unknown)
wati, Risma (Unknown)



Article Info

Publish Date
30 Dec 2024

Abstract

Abstract - Universities have an obligation to produce competent graduates. This can be measured from the graduation rate of students. The purpose of the analysis carried out is to predict graduation on time and find out indicators of problems that cause graduation not to be on time. Many factors influence students' late graduation, such as the student's marital status, the status of the student working or not working, the level of student understanding of the course material which can be seen from the student's GPA. Predicting student graduation is very important because this research can make a significant contribution both academically. Understand patterns or factors that influence student success. Provides insights for designing more effective educational interventions, such as academic tutoring. Based on the existing problems, it is necessary to have a system to predict student graduation rates based on existing variables. Attributes used are Name, Name, Gender, School of Origin, Study Program, Year of College Entry, Year of Graduation, Student Status, Marital Status, Age, IPS, GPA and Parent's Occupation. The method used is the Naive Bayes method. Comparison results were carried out using Excel and Rapidminer tools. The resulting accuracy level is 97,96% from 330 training data and 98 test data

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Journal Info

Abbrev

fortech

Publisher

Subject

Computer Science & IT

Description

Jurnal Fortech merupakan media publikasi terbitan Lembaga Penelitian dan Pengabdian Masyarakat (LP2M) STMIK Nurdin Hamzah Jambi yang berisi hasil penelitian para akademisi dan praktisi berkaitan dengan teknologi informasi dan komunikasi terbit sebanyak 2 kali dalam setahun di bulan April dan ...