Using Naive Bayes Algorithm to Students' bachelor Academic Performances Analysis

TL;DR

This paper applies the Naive Bayes classification algorithm to analyze and improve students' academic performance using data such as grades, attendance, and assignments, aiding both students and lecturers.

Contribution

It introduces a Naive Bayes-based classification approach for academic data mining to evaluate student performance and support academic progress.

Findings

Naive Bayes effectively classifies student performance data.

The method aids in identifying students needing academic support.

Supports academic evaluation for students and lecturers.

Abstract

Academic Data Mining was one of emerging field which comprise procedure of examined students details by different elements such as earlier semester marks, attendance, assignment, discussion, lab work were of used to improved bachelor academic performance of students, and overcome difficulties of low ranks of bachelor students. It was extracted useful knowledge from bachelor academic students data collected from department of Computing. Subsequently preprocessing data, which was applied data mining techniques to discover classification and clustering. In this study, classification method was described which was based on naive byes algorithm and used for Academic data mining. It was supportive to students along with to lecturers for evaluation of academic performance. It was cautionary method for students to progress their performance of study.