Digital Burnout Risk Classification Based on Doomscrolling and Fear of Missing Out Using the Mamdani Fuzzy Method - Matelda Yunanta Ambon; Rosmasari; Fahrul Agus (Indonesian Journal of Data and Science, 2026)
Intensive digital technology use among university students may trigger Digital Burnout, compounded by doom scrolling and Fear of Missing Out (FOMO). No systematic mechanism exists for automatically identifying students' Digital Burnout risk. This study classifies students' Digital Burnout levels into low, moderate, and high categories based on doom scrolling and FOMO. The Mamdani Fuzzy method was applied, with Doom scrolling and FOMO as inputs and Digital Burnout as the output, implemented in MATLAB Fuzzy Logic Toolbox. Data were collected from 414 students via an online self-report questionnaire, yielding 408 valid records (171 gamer, 237 general); all instruments were valid and reliable (Cronbach's Alpha: 0.947; 0.952; 0.964). Ground truth categories were derived from validated questionnaire scores, not clinical diagnosis or expert assessment. The system used nine IF–THEN rules with trapmf/trimf functions on [0,100] and centroid defuzzification, refined through twelve adjustment iterations.  Most students fell into the high Digital Burnout category (47.5%), followed by moderate (30.1%) and low (22.3%). The optimal configuration achieved 67.89% accuracy, with high precision but moderate recall for the High category (precision 0.9688, recall 0.6392), and higher accuracy for gamer (77.19%) than general respondents (61.18%). This study demonstrates the feasibility of combining doom scrolling and FOMO as Mamdani Fuzzy inputs for Digital Burnout risk classification. Given its moderate accuracy and reliance on self-reported rather than clinically validated labels, the model is an exploratory prototype rather than a validated screening instrument; further validation with independent samples and expert-reviewed rules is needed before practical application in student mental health services