Bridging the Gap: Enhancing Student Performance Analysis through Fuzzy Logic

Traditional methods in student performance evaluation usually depend on numerical scores ignoring and neglecting the subjectivity and complexity of learning. In order to examine student performance, this study explores the use of fuzzy logic, an approach that can include ambiguity and different degrees of membership. By investigating the effectiveness and use of a fuzzy logic system in capturing various aspects of student success that can go beyond the test scores. The system takes into account various factors such as hours studied, attendance, participation and sample question paper examined through the use of triangle membership function and fuzzy rules. Because fuzzy logic can handle ambiguous and inaccurate data, it offers a practical answer to these issues. This research surveys the existing literature and develops a theoretical framework to suggest a method for using fuzzy logic to the analysis of student performance. The study demonstrates how patterns, trends, and insights that traditional analysis methods can overlook can be found using fuzzy logic. Fuzzy logic can help researchers and ed-ucators gain a deeper understanding of students' academic performance, areas of strength, and areas for improvement. This can lead to more informed decisions and customized interventions in the field of education.