Sistem Penilaian Kesehatan Mental Mahasiswa Polibatam Berbasis Logika Fuzzy

Abstract

High academic pressure and an unbalanced lifestyle make students vulnerable to mental health disorders, while Politeknik Negeri Batam (Polibatam) does not yet have an objective early-detection system. This study designed a fuzzy logic-based mental health assessment system integrating stress level, measured with the Perceived Stress Scale (PSS-10), and lifestyle quality, measured with the FANTASTIC Lifestyle Checklist (FLC), through fuzzification, Min inference, and weighted-average defuzzification into three output categories: Good, Needs Attention, and High Risk. The system was implemented as a C# desktop application and tested on 30 active students using a quantitative, black-box approach. Manual calculation testing showed 93.33% agreement with the system output, confirming correct computational implementation. Consistency verification against the expert-validated rule base showed 80% agreement (24 of 30 data), although the High-Risk category was not represented in the test data. Clinical validation by a psychology expert of individual results was not conducted and remains a key limitation