Jurnal Ilmiah Multidisiplin Ilmu
Vol. 2 No. 1 (2025): Februari : Jurnal Ilmiah Multidisiplin Ilmu (JIMI)

KLASIFIKASI DATA MINING UNTUK MEMPREDIKSI KELULUSAN MAHASISWA MENGGUNAKAN METODE NAIVE BAYES

Jefri Jefri (Unknown)
Zaehol Fatah (Unknown)



Article Info

Publish Date
01 Feb 2025

Abstract

Data mining helps provide precise and careful decisions. Student graduation on time is one of the assessment points in the higher education accreditation process. However, student graduation cannot always be detected quickly, which can reduce the assessment of a university in the accreditation process. This problem arises to find out whether students will be able to graduate on time or not Classification method for predicting student graduates using the Naïve Bayes algorithm. Whether a student graduates on time or not, it is hoped that the results will provide information and input for the university in making future policies. From the results of this test, it was found that by applying the Naïve Bayes algorithm the system can predict student graduation in a timely manner. After comparing several literatures, it can be concluded that this method can be used for this prediction with an accuracy rate of 90%. This literature review is important as a supporting factor for research.

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Journal Info

Abbrev

jimi

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Subject

Other

Description

Jurnal Ilmiah Multidisiplin Ilmu (JIMI) dengan e-ISSN : 3047-2121, p-ISSN : 3047-2113, merupakan platform publikasi jurnal Karya suatu hasil penelitian orisinil atau tinjauan Pustaka yang ditulis oleh Dosen, mahasiswa dan atau Peneliti lainnya. Ruang lingkup karya yang diterbitkan mencakup ...