Analysis and Prediction of Student Academic Performance Using Machine Learning

Analyzing the academic performance of students is of utmost importance for academic institutions and educationists, so as to know the ways of improving individual student’s performance. The project analyzed the past results of students including their individual attributes including age, demographic...

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Bibliographic Details
Main Authors: Ajibola Oluwafemi Oyedeji, Abdulrazaq M Salami, Olaolu Folorunsho, Olatilewa R. Abolade
Format: Article
Language:English
Published: Andalas University 2020-03-01
Series:JITCE (Journal of Information Technology and Computer Engineering)
Subjects:
Online Access:http://jitce.fti.unand.ac.id/index.php/JITCE/article/view/51
Description
Summary:Analyzing the academic performance of students is of utmost importance for academic institutions and educationists, so as to know the ways of improving individual student’s performance. The project analyzed the past results of students including their individual attributes including age, demographic distribution, family background and attitude to study and tests this data using machine learning tools. Three models which are; Linear regression for supervised learning, linear regression with deep learning and neural network were tested using the test and train data with the Linear regression for supervised learning having the best mean average error (MAE).
ISSN:2599-1663