Prediction of final grade in linear algebra course with multiple linear regression approach

Andika Ellena Saufika Hakim Maharani; Siti Soraya; Gilang Primajati; Habib Ratu Perwira Negara; Ahmad Ahmad

doi:10.15294/ujm.v12i01.67448

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Affiliations

Andika Ellena Saufika Hakim Maharani
Universitas Bumigora

Siti Soraya
Universitas Bumigora

Gilang Primajati
Universitas Bumigora

Habib Ratu Perwira Negara
Universitas Bumigora

Ahmad Ahmad
Universitas Bumigora

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Prediction of final grade in linear algebra course with multiple linear regression approach

Andika Ellena Saufika Hakim Maharani ,
Siti Soraya ,
Gilang Primajati ,
Habib Ratu Perwira Negara ,
Ahmad Ahmad

Vol 12 No 1 (2023)

DOI 10.15294/ujm.v12i01.67448

Submitted: Mar 29, 2023

Published: May 20, 2023

Abstract

This article discusses the analysis of the final grade of Linear Algebra course with multiple linear regression approach. The study was conducted by collecting data on attendance, daily grades, and final grades from students of the Bumigora University Computer Science Program who took Linear Algebra courses in the odd semester of 2022/2023. Collected data were analyzed using multiple linear regression techniques. The purpose of this study is to determine the relationship between the variables that have a significant effect on student’s final grade and how to predict these variables using multiple linear regression models. The results of the analysis show that both independent variables, namely attendance and daily grades, have a significant impact on the dependent variable, namely student's final grade, with a significance value less than 0.05. The resulting multiple linear regression model can also be used to predict student’s final grade with an accuracy of 70.4%. Furthermore, the results of this analysis also show that daily grades has a greater influence than attendances in predicting final grades. The results of this study can provide useful information for lecturers in improving teaching and for students to improve their performance in the course.