Systematic Alternative Fuzzy Logic Evaluator (SAFLE) for student performance evaluation / Shirley Sinatra Gran, Tracy Adeline Ajol and Awang Nasrizal Awang Ali

• Main Authors: Gran, Shirley Sinatra, Ajol, Tracy Adeline, Awang Ali, Awang Nasrizal
• Format: Conference or Workshop Item
• Language: English
• Published: 2021
• Subjects: Performance. Competence. Academic achievement; Educational tests and measurements
• Online Access: https://ir.uitm.edu.my/id/eprint/56358/1/56358.pdf; https://ir.uitm.edu.my/id/eprint/56358/
• Institution: Universiti Teknologi Mara

Students' overall performance at school is essentially evaluated based on academic accomplishment. However, in high school or working environments, students must excel in other soft skills such as leadership, communication, and critical thinking. To evaluate criteria for student performance, for example, student behavior, which does not involve quantitative performance like academic scores, decision-making is critical. The assessment during the process of evaluation usually involves individuals with different opinions and thoughts. Therefore, the decision-making made based on human judgment may sometimes be time-consuming and unfair. Hence, a Systematic Alternative Fuzzy Logic Evaluator (SAFLE) is introduced to evaluate students' performance at school, particularly in identifying eligible students as the best student by implementing the fuzzy logic approach. The proposed evaluation also intends to simplify the evaluator's tasks due to time and fairness. The attribute measured includes the examination score, roles and responsibilities held in schools, and student's behaviour in school. The data is evaluated computationally using the Fuzzy Logic Toolbox in MATLAB. If-then rules are used as one way to identify the best student. The rules serve to ease the evaluator's decision-making by categorizing students into more flexible membership functions. The result obtained shows that the Fuzzy Logic Approach proposed can present an alternative systematic evaluation in selecting the best student to be awarded. The Fuzzy Logic approach can differentiate the score obtained and categorize students in the belongingness in the membership function.