Digital Burnout Risk Classification Based on Doomscrolling and Fear of Missing Out Using the Mamdani Fuzzy Method

Matelda Yunanta Ambon; Rosmasari; Fahrul Agus

doi:10.56705/ijodas.v7i2.442

Authors

Matelda Yunanta Ambon Universitas Mulawarman
Rosmasari Universitas Mulawarman
Fahrul Agus Universitas Mulawarman

DOI:

https://doi.org/10.56705/ijodas.v7i2.442

Keywords:

Classification, Digital Burnout, Doomscrolling, Fear of Missing Out, Fuzzy Mamdani

Abstract

Introduction: Intensive digital technology use among university students may contribute to Digital Burnout, particularly when accompanied by doomscrolling and Fear of Missing Out (FOMO). This study classifies Digital Burnout risk into low, moderate, and high categories using these two digital-behavior factors. Method: A Mamdani Fuzzy Inference System was implemented in MATLAB using Doomscrolling and FOMO as inputs and Digital Burnout as the output. Data were collected through validated self-report questionnaires from 414 students, resulting in 408 valid records. The system employed nine IF–THEN rules, trapezoidal and triangular membership functions within a normalized [0,100] domain, centroid defuzzification, and twelve parameter-adjustment iterations. Results and Discussion: The ground-truth distribution showed that 47.5% of students were categorized as having high Digital Burnout, 30.1% moderate, and 22.3% low. The optimal fuzzy configuration achieved 67.89% accuracy and a macro F1-score of 0.6725. The High category achieved very high precision of 0.9688 but moderate recall of 0.6392, indicating that some high-risk students remained undetected. Classification accuracy was higher among gamers (77.19%) than general respondents (61.18%). Conclusion: The Mamdani Fuzzy approach demonstrates the feasibility of classifying Digital Burnout risk from Doomscrolling and FOMO; however, its moderate accuracy and reliance on self-reported, non-clinical labels indicate that it should be considered an exploratory prototype requiring independent validation and expert-reviewed rules before practical deployment.

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