The modelling of earthquake magnitude in the southern part of Java Island using geographically weighted regression

Sediono -, M. Fariz Fadillah Mardianto, Siti Maghfirotul Ulyah, Alvito Aryo Pangestu, Rita Susanti, Haydar Arsy Firdaus, Christopher Andreas

Abstract


One of the aspect of the Sustainable Development Goals (SDGs) is to build the sustainable cities and communities, making cities inclusive, safe, strong and sustainable. One form of sustainable development, that is a good city, apart from a green city, is development that is alert and responsive to disasters. Earthquakes are one of the natural disasters that often occur in Indonesia and cause many casualties. The purpose of this study is to obtain an overview of the earthquake magnitude and the factors that influence it in the southern part of Java Island using Geographically Weighted Regression (GWR). The data used is earthquake magnitude and depth which obtained from the Indonesian Meteorology, Climatology and Geophysics Agency (BMKG) website. The data is the earthquake that occurred in the southern part of Java Island in 2019-2021. The modelling of earthquake magnitude in southern Java Island using GWR based on the best weighted of Adaptive Bisquare Kernel produced a  value of 98.96% and an MSE of 0.002 and an optimal bandwidth of 4. The results of this analysis can be used as a reference in making disaster mitigation solutions and in determining the location of airports and ports in an area.

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Published: 2022-02-07

How to Cite this Article:

Sediono -, M. Fariz Fadillah Mardianto, Siti Maghfirotul Ulyah, Alvito Aryo Pangestu, Rita Susanti, Haydar Arsy Firdaus, Christopher Andreas, The modelling of earthquake magnitude in the southern part of Java Island using geographically weighted regression, Commun. Math. Biol. Neurosci., 2022 (2022), Article ID 13

Copyright © 2022 Sediono -, M. Fariz Fadillah Mardianto, Siti Maghfirotul Ulyah, Alvito Aryo Pangestu, Rita Susanti, Haydar Arsy Firdaus, Christopher Andreas. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Commun. Math. Biol. Neurosci.

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