Unnes Journal of Mathematics
Vol 12 No 1 (2023)

Prediction of Final Grade in Linear Algebra Course with Multiple Linear Regression Approach

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)



Article Info

Publish Date
20 May 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.

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Journal Info

Abbrev

ujm

Publisher

Subject

Mathematics

Description

Unnes Journal of Mathematics (UJM) publishes research issues on mathematics and its apllication. The UJM processes manuscripts resulted from a research in mathematics and its application scope, which includes. The scopes include research in: 1. Algebra 2. Analysis 3. Discrete Mathematics and Graph ...