An Enhanced Systematic Student Performance Evaluation Based on Fuzzy Logic Approach for Selection of Best Student Award

• Main Authors: Ajol, T.A (Author), Gran, S.S (Author), Kanyan, A. (Author), Lajim, S.F (Author)
• Format: Article
• Language: English
• Published: UiTM Press, 2020
• Subjects: Evaluation; Fuzzy logic; Initiative; Leadership; Student’s Award
• Online Access: View Fulltext in Publisher; View in Scopus
• ISBN: 18237797 (ISSN)
• ISSN: 18237797 (ISSN)
• DOI: 10.24191/ajue.v16i4.11932

The Best Student Award is one of the incentives initiated by an institution to identify potential students who are not only excellent academically, but also possess great leadership skills. Moreover, these skills may also be enhanced which subsequently contribute to the future of society. Nonetheless, one of the greatest challenges faced by evaluators in the selection process include uncertainty and imprecise data in measuring the students’ leadership competencies. Thus, this paper proposes the development of Initiative-Systematic Performance Evaluation (I-SPE) as an initiative tool to measure students’ competencies based on Fuzzy Logic Approach. The study focuses on the selection of the best student based on data collected from a leadership programme – Program Kepimpinan Pewaris Bangsa (PKPB) conducted at Universiti Teknologi MARA (UiTM) Cawangan Sarawak, Mukah Campus. In the current practice, tie and time-consuming challenges due to the subjectivity and complexity of measurement criteria are involved. Therefore, I-SPE will assist to provide an improved decision-making solution to evaluators during the evaluation process. Fuzzy logic tools used to develop I-SPE allow the experts to introduce any uncertainty and subjectivity into the evaluation system. The development of fuzzy rules in this model is based on five selected attributes, which include leadership, communication, teamwork, discipline and CGPA. Results obtained indicate that the proposed model I-SPE is able to improve decision-making efficiency that would lead to fairness in selecting the best candidate as compared to the conventional method. © 2020. All Rights Reserved.