Decision Support System for Early Detection of Depression Risk Based on Lifestyle Patterns Using the ROC-WASPAS Method - Fadlina; Sugi Hartono Sinambela (The IJICS (International Journal of Informatics and Computer Science), 2026)
This study develops a decision-support model for prioritizing lifestyle-based depression risk indicators using Rank Order Centroid (ROC) weighting and Weighted Aggregated Sum Product Assessment (WASPAS). The model evaluates five respondents against five criteria: stress level, sleep duration, social interaction, dietary pattern, and physical activity. Criterion priorities were converted into ROC weights, after which the decision matrix was normalized according to cost and benefit orientation. WASPAS then combined the weighted sum and weighted product components using an equal aggregation coefficient. Stress received the largest weight (0.456), followed by sleep duration (0.256), social interaction (0.156), dietary pattern (0.090), and physical activity (0.040). The final preference scores placed A1 first (0.569), followed by A3 (0.557), A2 (0.519), A5 (0.502), and A4 (0.434). These scores represent relative lifestyle profiles within the small study sample; they do not constitute a clinical diagnosis of depression. The model demonstrates a transparent calculation workflow that may support preliminary risk prioritization when its criteria, scales, and weights have been validated by mental-health professionals. Future work should use a larger sample, a validated depression instrument, sensitivity analysis, and external validation before practical screening is considered.