A Blockchain-based Landslide Mitigation Recommendation System for Decision-Making - Hindarto, Djarot; Hariadi, Mochamad; Rachmadi, Reza Fuad (Engineering, Technology & Applied Science Research, 2025)
Landslides are catastrophic natural disasters that could threaten the structural integrity of a building, imposing hazards to engineering and human life. This study proposes a TOPSIS landslide disaster mitigation recommendation system integrated with blockchain. New approaches to data provenance, transparency, and informed decision-making are explored in the context of geospatial blockchain. The decision-making process is carried out using the multicriteria evaluation method, which considers soil stability, rainfall, vegetation density, proximity to rivers, and slope. The results yielded promising precision, recall, accuracy, and F1 scores (91%, 93%, 95%, and 95%, respectively), suggesting that the model could make accurate and impartial prioritization predictions. Blockchain ensures data transparency, immutability, and security, and TOPSIS ranks mitigation strategies from worst to best to determine the better solution. The proposed approach is essential to predict regions that are prone to landslides and enables the appropriate management of relaxation measures. This application of blockchain technology can provide trust, reliability, and speed in decision-making while reducing landslides.