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The Application of Spatial Analysis and Time Series in Modeling the Frequency of Earthquake Events in Bengkulu Province
Author(s) -
Fachri Faisal,
Pepi Novianti,
José Rizal
Publication year - 2018
Publication title -
aceh international journal of science and technology
Language(s) - English
Resource type - Journals
eISSN - 2503-2348
pISSN - 2088-9860
DOI - 10.13170/aijst.7.2.8656
Subject(s) - variogram , kriging , autoregressive–moving average model , autoregressive model , time series , statistics , interpolation (computer graphics) , series (stratigraphy) , mathematics , computer science , geology , artificial intelligence , motion (physics) , paleontology
This study provides an overview in combining spatial analysis and time series analysis to model the frequency of earthquake. The aim of this research is to apply the spatial statistical analysis and time series analysis in estimating semivariogram parameters for the next four steps. The data in this study is secondary data that has been validated based on sources that publish parameters of earthquake events. Looking at the characteristics of the earthquake frequency frequency data, there are spatial and time elements. The method used in this research is interpolation kriging and Autoregressive Moving Average (ARMA) model. The semivariogram models used in kriging interpolation are: Spherical, Exponential, Gaussian, and Linear. The parameters of the semivariogram model are modeled using ARMA time series analysis adjusted to the model diagnostic results. To measure of fit model is used Mean Square Error (MSE). The result of research is a suitable semivariogram model to be applied in the modeling of earthquake events is the Spherical model. While each parameter is estimated using ARMA model (2,2) with different coefficient estimation value.

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