Prediction of Students’ Major Selection Using the Fuzzy Sugeno Method Based on Report Card Grades

Abstract

This study aims to develop a student achievement prediction system based on the Fuzzy Sugeno method using average report card scores to support science or social studies specialization recommendations. The data were obtained from student report cards at SMA 1 Toho in Microsoft Excel format and processed through fuzzification, inference, and defuzzification stages using triangular membership functions to produce crisp values and achievement categories. The system was implemented using the Python programming language and evaluated for result consistency. The findings indicate that the Fuzzy Sugeno method can objectively predict student achievement and support data-driven decision making in determining student specialization.