EVALUATION THE USE OF ANFIS IN PREDICTING STUDENT’S PERFORMANCE

Khudhair, Zainab R; Raheema, Mithaq; Salman, Jabbar

doi:10.63463/kjes1088

	EVALUATION THE USE OF ANFIS IN PREDICTING STUDENT’S PERFORMANCE
Kerbala Journal for Engineering Sciences (KJES)
Volume 3, Issue 3, September 2023, Pages 101-113 PDF (1.17 M)
Document Type: Research Article
DOI: 10.63463/kjes1088
Authors
Zainab R khudhair^* ¹; Mithaq Raheema²; Jabbar Salman³
¹Deprtment OF Electrical and Electronic Engineering, University of Kerbala
²College of Engineering/ University of Kerbala, Kerbala, Iraq.
³PROSTBETIC&ORTHETIC Eng. College of Engineering Karbala University
Abstract
This article suggests the implementation of an online distance education system as a way to enhance the academic performance of students. It emphasizes the importance of monitoring and predicting the Learning Academic Performance (LAP) to enable appropriate adjustments and ensure continuous academic progress. In this education mode, predicting LAP accurately is a challenging task. Adaptive Neuro-Fuzzy Inference System (ANFIS), executed by ‘MATLAB R2020a’, creates systems that can successfully achieve the aim. The suggested ANFIS models were used to forecast students' Cumulative Grade Point Averages (CGPAs). The interactions between input variables and their associated impacts on the output values were further investigated using the models. The results showed high accuracy levels, varying scores from 83.8% to 90%. Additionally, this study found a significant correlation between CGPA and the examination scores, indicating a direct proportional relationship. These findings emphasize the crucial role of examination scores in evaluating academic performance and the importance for students to prioritize and focus on their exam performance.
Keywords
: Adaptive Neuro-Fuzzy Inference System (ANFIS); Performance Prediction; and Cumulative Grade Point Average

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