Expert system using fuzzy logic and its relationship with the recommendation of extracurricular activities in high school students in Trujillo (#868)

Authors

Rondon Pozo, Jordan Angel

Alfaro Quispe, Pablo Efrain

Abstract

The main objective of this study is to develop an expert system based on fuzzy logic to recommend personalized extracurricular activities to high school students. For this purpose, Mamdani's fuzzy inference method was used, implemented in Python with the Skfuzzy and Tkinter libraries, and validated by means of questionnaires applied to a sample of 30 students. The results revealed that the system provides recommendations aligned with the interests and skills of the users, with high levels of satisfaction and perception of academic relevance. In addition, fuzzy logic was found to provide flexibility and accuracy compared to traditional approaches, providing multiple options suitable for each student. In conclusion, the fuzzy logic-based expert system proved to be an effective tool to support the choice of extracurricular activities, contributing significantly to students' personal and academic development.