Developing a Fuzzy Logic and Sensitivity Analysis Model to Estimate Financial Loss from Social Conflict and Natural Disaster Risks in Hillside Construction Project
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Hillside construction projects face external risks from community issues and slope problems such as landslides, which often cause cost overruns. However, current tools like risk matrices do not provide accurate cost estimates. This study develops a model that converts expert judgments on social conflict (RS) and natural-disaster risks (RB) into expected financial loss as a percentage cost overrun. The model used frequency and consequence ratings from 30 stakeholders, validated by six experts (I-CVI: 0.83–1.00; S-CVI/Ave: 0.90–0.92). Internal consistency was confirmed (Cronbach's α: 0.759–0.873). Scores were combined using weighted geometric mean (ω_F = 0.318; ω_C = 0.682) and processed by a Mamdani fuzzy inference system with triangular/trapezoidal membership functions and a 3×3 rule base. Tested on a hillside villa project in Lombok, Indonesia, the model estimated loss at 12.75%, close to the actual overrun of 11.65% (MAPE = 9.42%). Sensitivity analysis shows RB dominates near baseline, while RS exhibits threshold effects at higher levels. Cost-benefit analysis reveals mitigation value depends on how much KF can be reduced per mitigation cost. This framework enables integration of qualitative risk assessment into early contingency planning for hillside construction projects.
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