Klasifikasi Data Mining Untuk Memprediksi Kelulusan Mahasiswa Menggunakan Metode Naive Bayes
Year: 2025
Type: article
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.
Source: Jurnal Ilmiah Multidisiplin Ilmu
DOI: 10.69714/mhjq1v85
Authors: Jefri Jefri, Zaehol Fatah
Institution: Universitas Ibrahimy
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: bronze
OpenAlex ID: W4407063955