Adaptive Neural Fuzzy Inference System and Automatic Clustering For Earthquake Prediction in Indonesia - Mohammad Nur Shodiq,Dedy Hidayat Kusuma,Mirza Ghulam Rifqi,Ali Ridho Barakbah,Tri Harsono (International Conference on Industrial Revolution for Polytechnic Education, 2020)
Earthquake is a type of natural disaster. The Indonesian archipelago is located in the world's three mega plates, they are Australian plate, Eurasian plate, and Pacific plate. Therefore, it is possible for applied of earthquake risk of mitigation. One of them is to provide information about earthquake occurrences. This information is used for spatiotemporal analysis of earthquakes. This paper presented Spatial Analysis of Magnitude Distribution for Earthquake Prediction using adaptive neural fuzzy inference system (ANFIS) based on automatic clustering in Indonesia. This system has 3 main sections: (1) Data preprocessing, (2) Automatic Clustering, (3) Adaptive Neural Fuzzy Inference System. For experimental study, earthquake data is obtained Indonesian Agency for Meteorological, Climatological, and Geophysics (BMKG) and the United States Geological Survey’s (USGS), the year 2010-2017 in the location of Indonesia. Automatic clustering process produces The optimal number of cluster, that is 7 clusters. Each cluster will be analyzed based on earthquake distribution. its calculate the b value of earthquake to get the seven seismicity indicators. Then, implementation for ANFIS uses 100 training epochs, Number of MFs is 2, MFs type input is gaussmf. The ANFIS result showed that the system can predict the non-occurrence of aftershocks with the average performance of 70%