Implementation of Bayesian Simulation for Earthquake Disaster Risk Analysis in Indonesia based on Gutenberg Richter Model and Copula Method

Abstract

Indonesia is a country prone to earthquakes because it is located in the Pasific ring of fire area. The earthquakes caused a lot of damages and casualties. In this paper, we use Bayesian Simulation on Gutenberg Richter model and Copula method to estimate the risk parameters of earthquake, specifically the probability and the recurrence (return) period of an earthquake occurrence in Indonesia. Those risk parameters are estimated from dependence structure of frequency and magnitude of earthquakes. The dependence structure can be determined by using Gutenberg Richter model and Copula method. The Gutenberg Richter model is a model based on linear regression used to determine dependence structure, while the Copula method is a statistical method used to determine dependence structure that ignores linearity and normality assumptions of data. Bayesian Simulation is a method used to estimate parameters based on simulation. The data used is an annual data of frequency and magnitude (magnitude ≥ 4 Richter Scale) of earthquakes occur in Indonesia for 4 years from Meteorological, Climatological, and Geophysical Agency of Indonesia. There are several steps of analysis to be performed: firstly, we perform regression analysis of frequency and magnitude of the earthquakes to determine Gutenberg Richter Model; secondly, we perform Copula analysis; thirdly, we estimate probability and the recurrence (return) period of an earthquake occurrence using Bayesian Simulation based on the result of step one and two. The result indicates Bayesian Simulation can estimate risk parameters very well.