Development of a Fuzzy Logic Model for Tsunami Early Detection Using Tunami F1 on the Southern Coast of Yogyakarta International Airport, Jogja

Tsunami disaster mitigation requires a reliable early warning system to reduce traumatic impacts and material losses. This study develops a fuzzy logic model for early tsunami detection by integrating wave height (SSH) and estimated tsunami arrival time (ETATSU) parameters. The model is combined with the TUNAMI F1 simulation, which considers seabed topography and fluid dynamics. Simulations were conducted on 36 earthquake scenarios on the southern coast near Yogyakarta International Airport (YIA). The results show that the model successfully classifies tsunami risks into three categories: alert, standby, and emergency, with an overall accuracy of 83.3%. Some scenarios showed invalid results at high magnitudes (Mw ≥ 8.5). This research improves the accuracy of tsunami early warning systems, potentially saving more lives and minimizing the impact of disasters.