PREDICTING STUDENT GRADUATION USING THE FUZZY TSUKAMOTO METHOD IN COMPUTER SCIENCE STUDY PROGRAM STUDENTS CLASS OF 2022

Upuy, Doms
Suhardin, Askin
Sapri, Ismu Iqbal

Indonesian Journal on Data Science
Vol. 2 No. 2 (2024): Indonesian Journal On Data Science

This research aims to help optimize resources by designing a system that can be used to help predict student graduation at Pattimura University. The system method used is the Tsukamoto fuzzy method. Tsukamoto's method is an extension of monotonic reasoning. In the Tsukamoto method, each consequence of a rule in the form of IF-THEN must be represented by a fuzzy set with a monotonic membership function. As a result, the inference output from each rule is given firmly (crisp) based on the ?-predicate (fire strength). The final result is obtained using a weighted average. The result of this research is a student graduation prediction system to optimize good results and avoid errors that occur when predicting student graduation.