Determinants of Graduates Employability among Alumni at UiTM Seremban Campus: A Multiple Linear Regression Approach

Graduate employability has become an important issue as the increasing number of graduates has intensified competition in the labour market. Understanding the factors that influence graduates' employability is essential for higher education institutions to enhance graduates' career readiness and reduce graduate unemployment. Therefore, this study aimed to examine the determinants of graduates' employability among alumni of the Faculty of Computer and Mathematical Sciences (FSKM), Universiti Teknologi MARA (UiTM) Seremban Campus. Specifically, the study investigated the relationship between gender, Cumulative Grade Point Average (CGPA), English language skills, technical skills and programme of study with graduates' employment duration. A quantitative research design was employed and data were collected using a structured questionnaire distributed through online platforms. A total of 374 valid responses were obtained after data cleaning. Following the removal of influential observations, 343 observations were retained and analysed using SAS On Demand for Academics. Descriptive statistics and Multiple Linear Regression (MLR) were employed to analyse the data. The findings revealed that CGPA, gender, BSc Management Mathematics and BSc Mathematics were significant predictors, while English language skills, technical skills and BSc Mathematics with Business Economics were not statistically significant. The final regression model was statistically significant, F (7, 335) = 14.18, p < .0001, and explained 22.86% of the variation in the square-root-transformed employment duration (R² = 0.2286, Adjusted R² = 0.2125). The findings suggest that practical competencies and the relevance of academic programmes to industry needs play a more important role in improving graduate employability than demographic or academic achievement alone. It is hoped that the findings of this study will assist universities, policymakers, and future researchers in developing strategies to improve graduate employability and strengthen the alignment between higher education and labour market demands.

Graduate Employability, Determinants, Multiple Linear Regression, Significant Variables

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