Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Journal of Statistics and Data Science
Meiwidian, Muhamad Iqbal
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Other

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Earthquake Clustering Using the CLARA Method and Modeling Using the Inhomogeneous Spatial Cox Processes Method in the Ambon Region: Earthquake Clustering Using the CLARA Method and Modeling Using the Inhomogeneous Spatial Cox Processes Method in the Ambon Region Meiwidian, Muhamad Iqbal; Crisdianto, Riki; Rini, Dyah Setyo
Journal of Statistics and Data Science Vol. 2 No. 2 (2023)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jsds.v2i2.30249

Abstract

Earthquakes are natural events whose time and place cannot be predicted. Ambon is the largest city in the Maluku Islands region and is the center of development and the capital of Maluku Province. This research will group earthquake events, analyze the characteristics of earthquake events, create earthquake zones and map them using CLARA cluster analysis, and create modeling that will look at the risk of earthquake events in a location based on distance to faults and subduction zones using the Inhomogeneous Neyman-Scott Cox Process. The data used is data on earthquake events in the Ambon region obtained from the United States Geological Survey (USGS) catalog from January 1926 to December 2022, with a depth of ≤360.1 Km and a magnitude of ≥4 Mw. Grouping earthquake events in the Ambon area using CLARA cluster analysis obtained 2 groups of earthquake clusters with an optimal silhouette score of 0.7430. The model obtained in this earthquake research is not good because it is based on the K-function value plot of the original data which is far from the modeling K-function value plot.
Co-Authors Crisdianto, Riki Rini, Dyah Setyo