Classification of students based on quality of life and academic performance by using support vector machine
Raihana, Z1, Farah Nabilah, A.M2.
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.
Affiliation:
- Universiti Teknologi MARA, Malaysia
- Universiti Teknologi MARA, Malaysia
Download this article (This article has been downloaded 206 time(s))