Rainfall Prediction Using Fuzzy Logic Method For Early Warning System In Flood Disaster Mitigation In Nganjuk Muhammad Shofwan Donny Cahyono 1,* , Leonardus Setia Budi Wibowo 2 , Yoga Alif Kurnia Utama 3 {shofwandonny@widyakartika.ac.id 1 , leon004@brin.go.id 2 , yoga.alif1@gmail.com 3 } Civil Engineering, Faculty Engineering, Widya Kartika University, Surabaya, Indonesia 1 Civil Engineering, Faculty Engineering, Widya Kartika University, Surabaya and National Research and Innovation Agency, Indonesia 2 Electrical Engineering, Faculty Engineering, Widya Kartika University, Surabaya, Indonesia 3 Abstract. In general, flooding often causes problems in the form of flood disasters. This is because the flooding of shipments is unpredictable and causes a large area of impact. This problem will certainly have an impact on various life activities, such as threatened public safety, the emergence of congestion, and a decrease in agricultural, livestock, and fishery production. The cause of overland flow is the overflowing river in the upstream area due to high intesity of rainfall, therefore an early warning of flood predictions is needed to prepare to minimize the impact of flooding. One of the effective solutions is rainfall prediction for flood early detection systems. This study aims to predict the weather optimally and apply it to flood early warning system applications using fuzzy logic methods. The predicted rainfall intensity of the fuzzy logic model has an error rate of 4.58%. Keywords: Flood, Fuzzy logic, Early warning system 1 Introduction Climate change, which has occurred in recent decades, makes impacts upon many countries in the world, including Indonesia. One of the effects caused by this natural phenomenon is the shifting seasons which affect the rainfall patterns. Because it resulted in increased depth of rainfall in a short time. The accumulation of fixed annual rainfall within a short duration of rain will trigger an increase in flood intensity in Indonesia [1]. ICO-SEID 2022, November 23-24, Jakarta, Indonesia Copyright © 2023 EAI DOI 10.4108/eai.23-11-2022.2341570