Classification of students based on quality of life and academic performance by using support vector machine / Raihana Zainordin and A.M. Farah Nabilah

Most studies done in the past on factors affecting academic performance did not touch on quality of life factor. Also, most studies only used correlation and regression analysis. Not many studies used classification analysis. Hence, this study aimed to classify students based on quality of life and...

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Main Authors: Zainordin, Raihana, A.M., Farah Nabilah
Format: Article
Language:English
Published: Universiti Teknologi MARA, Negeri Sembilan 2018
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/29644/
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author Zainordin, Raihana
A.M., Farah Nabilah
author_facet Zainordin, Raihana
A.M., Farah Nabilah
author_sort Zainordin, Raihana
building UiTM Institutional Repository
collection Online Access
description Most studies done in the past on factors affecting academic performance did not touch on quality of life factor. Also, most studies only used correlation and regression analysis. Not many studies used classification analysis. Hence, this study aimed to classify students based on quality of life and academic performance. Students’ quality of life was measured by using WHOQOL-BREF questionnaire which consists of five quality of life domains namely physical health, psychological health, social relationship, environment and overall quality of life whereas the academic performances were represented by cumulative grade point average (CGPA). The selected sample for this study was 60 Universiti Teknologi MARA (UiTM) Perlis students from Bachelor of Science (Hons.) Management Mathematics program. This study applied support vector machine (SVM) method for classifying the students. The results for each quality of life domain showed that students with both low and high academic performance were classified into high academic performance class. The same result was obtained when all domains were combined. All models showed high accuracy which implied that the classification made by SVM were strongly correct. The findings of this study demonstrated that quality of life plays an important role in students’ academic performance.
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spelling uitm-296442020-04-21T00:16:52Z https://ir.uitm.edu.my/id/eprint/29644/ Classification of students based on quality of life and academic performance by using support vector machine / Raihana Zainordin and A.M. Farah Nabilah joa Zainordin, Raihana A.M., Farah Nabilah Life style QA Mathematics Mathematical statistics. Probabilities Most studies done in the past on factors affecting academic performance did not touch on quality of life factor. Also, most studies only used correlation and regression analysis. Not many studies used classification analysis. Hence, this study aimed to classify students based on quality of life and academic performance. Students’ quality of life was measured by using WHOQOL-BREF questionnaire which consists of five quality of life domains namely physical health, psychological health, social relationship, environment and overall quality of life whereas the academic performances were represented by cumulative grade point average (CGPA). The selected sample for this study was 60 Universiti Teknologi MARA (UiTM) Perlis students from Bachelor of Science (Hons.) Management Mathematics program. This study applied support vector machine (SVM) method for classifying the students. The results for each quality of life domain showed that students with both low and high academic performance were classified into high academic performance class. The same result was obtained when all domains were combined. All models showed high accuracy which implied that the classification made by SVM were strongly correct. The findings of this study demonstrated that quality of life plays an important role in students’ academic performance. Universiti Teknologi MARA, Negeri Sembilan 2018 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/29644/1/29644.pdf Zainordin, Raihana and A.M., Farah Nabilah (2018) Classification of students based on quality of life and academic performance by using support vector machine / Raihana Zainordin and A.M. Farah Nabilah. (2018) Journal of Academia <https://ir.uitm.edu.my/view/publication/Journal_of_Academia.html>, 6 (1). pp. 45-52. ISSN 2289-6368 https://nsembilan.uitm.edu.my/joacns/
spellingShingle Life style
QA Mathematics
Mathematical statistics. Probabilities
Zainordin, Raihana
A.M., Farah Nabilah
Classification of students based on quality of life and academic performance by using support vector machine / Raihana Zainordin and A.M. Farah Nabilah
title Classification of students based on quality of life and academic performance by using support vector machine / Raihana Zainordin and A.M. Farah Nabilah
title_full Classification of students based on quality of life and academic performance by using support vector machine / Raihana Zainordin and A.M. Farah Nabilah
title_fullStr Classification of students based on quality of life and academic performance by using support vector machine / Raihana Zainordin and A.M. Farah Nabilah
title_full_unstemmed Classification of students based on quality of life and academic performance by using support vector machine / Raihana Zainordin and A.M. Farah Nabilah
title_short Classification of students based on quality of life and academic performance by using support vector machine / Raihana Zainordin and A.M. Farah Nabilah
title_sort classification of students based on quality of life and academic performance by using support vector machine / raihana zainordin and a.m. farah nabilah
topic Life style
QA Mathematics
Mathematical statistics. Probabilities
url https://ir.uitm.edu.my/id/eprint/29644/
https://ir.uitm.edu.my/id/eprint/29644/