SISTEM PENDUKUNG KEPUTUSAN TINGKAT STRES MAHASISWA ELEKTRO DENGAN METODE FUZZY MAMDANI DI UNIVERSITAS NUSA PUTRA SUKABUMI

This study aims to develop a predictive model of student stress levels based on academic data using a fuzzy logic approach. This method is implemented in the Python programming language by utilizing the scikit-fuzzy library. The data used include the cumulative grade point average (GPA), attendance rate, and semester study load (SKS) of students. The fuzzy inference model is used to determine the level of student stress based on these variables. This study was conducted through several stages, including data collection from structured questionnaires, data processing, building a fuzzy inference model, and model evaluation. The results of this model are then compared with the results of the questionnaire to evaluate its accuracy and suitability. Analysis of the results shows that the fuzzy logic model is able to provide estimates that are consistent with the results of the questionnaire, with an accuracy level of 80%. However, there are some differences in the results indicating that there are other factors that need to be considered in the model. Nevertheless, this model provides a strong foundation for further development in understanding and managing student stress. In conclusion, this study shows the potential for using fuzzy logic in modeling student stress levels based on academic data. With further adjustments and development, this model can be a valuable tool in supporting efforts to help student well-being in the academic environment.
Keywords: stress level, students, fuzzy logic, Decision Support System, Academic Well-being, Python, Nusa Putra University.