MAPPING EARTHQUAKE MAGNITUDES IN BENGKULU PROVINCE AND SURROUNDING AREAS USING ROBUST ORDINARY KRIGING

Bengkulu Province, situated in a subduction zone between the Indo-Australian and Eurasian plates, is highly susceptible to significant seismic activity, including major earthquakes in 2000 and 2007 with magnitudes exceeding 7. This research investigates the geographical distribution of earthquake magnitudes in Bengkulu Province and surrounding areas from 2000 to 2023. Understanding these spatial patterns is crucial for enhancing disaster preparedness and risk mitigation strategies in this high-risk region. Previous studies on earthquake distribution in Indonesia have provided valuable insights but often struggle with outliers and data variability, limiting their accuracy. Conventional Ordinary Kriging methods, though widely used, are sensitive to outliers, leading to potential inaccuracies. This study addresses these limitations by applying a robust Ordinary Kriging approach, which effectively mitigates the influence of outliers, thereby improving prediction reliability. The research utilizes earthquake data, including geographical coordinates and recorded magnitudes. It applies both classical and robust experimental semivariograms (Cressie-Hawkins) to model the spatial structure using theoretical variogram models—spherical, exponential, and Gaussian. The best-fit model is determined based on the lowest root mean square error (RMSE), ensuring accurate representation of spatial patterns. The results demonstrate that robust Ordinary Kriging accurately maps the spatial distribution of earthquake magnitudes, revealing clusters of higher magnitude events in specific regions of Bengkulu Province. These findings identify high-risk areas, providing essential data for disaster mitigation and risk management planning. This study significantly contributes to the field of seismology and geostatistics by enhancing the accuracy of magnitude distribution mapping. The resulting maps support local governments, urban planners, and disaster response organizations in developing more effective mitigation strategies, improving infrastructure resilience, and strengthening early warning systems. Ultimately, this research aims to foster safer, more prepared communities in Bengkulu Province and beyond.

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Publication Details

Journal
BAREKENG JURNAL ILMU MATEMATIKA DAN TERAPAN
Published
2025-07-01
DOI
https://doi.org/10.30598/barekengvol19iss3pp1537-1552
Citations
1
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
2.48

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article

MAPPING EARTHQUAKE MAGNITUDES IN BENGKULU PROVINCE AND SURROUNDING AREAS USING ROBUST ORDINARY KRIGING

Swita Baki, Aang Nuryaman, Fachri Faisal, Mulia Astuti
1 citations
BAREKENG JURNAL ILMU MATEMATIKA DAN TERAPAN
Geochemistry and Geologic Mapping
2.48
article

MAPPING EARTHQUAKE MAGNITUDES IN BENGKULU PROVINCE AND SURROUNDING AREAS USING ROBUST ORDINARY KRIGING

Swita Baki, Aang Nuryaman, Fachri Faisal, Mulia Astuti
article en
1 citations

Abstract

Bengkulu Province, situated in a subduction zone between the Indo-Australian and Eurasian plates, is highly susceptible to significant seismic activity, including major earthquakes in 2000 and 2007 with magnitudes exceeding 7. This research investigates the geographical distribution of earthquake magnitudes in Bengkulu Province and surrounding areas from 2000 to 2023. Understanding these spatial patterns is crucial for enhancing disaster preparedness and risk mitigation strategies in this high-risk region. Previous studies on earthquake distribution in Indonesia have provided valuable insights but often struggle with outliers and data variability, limiting their accuracy. Conventional Ordinary Kriging methods, though widely used, are sensitive to outliers, leading to potential inaccuracies. This study addresses these limitations by applying a robust Ordinary Kriging approach, which effectively mitigates the influence of outliers, thereby improving prediction reliability. The research utilizes earthquake data, including geographical coordinates and recorded magnitudes. It applies both classical and robust experimental semivariograms (Cressie-Hawkins) to model the spatial structure using theoretical variogram models—spherical, exponential, and Gaussian. The best-fit model is determined based on the lowest root mean square error (RMSE), ensuring accurate representation of spatial patterns. The results demonstrate that robust Ordinary Kriging accurately maps the spatial distribution of earthquake magnitudes, revealing clusters of higher magnitude events in specific regions of Bengkulu Province. These findings identify high-risk areas, providing essential data for disaster mitigation and risk management planning. This study significantly contributes to the field of seismology and geostatistics by enhancing the accuracy of magnitude distribution mapping. The resulting maps support local governments, urban planners, and disaster response organizations in developing more effective mitigation strategies, improving infrastructure resilience, and strengthening early warning systems. Ultimately, this research aims to foster safer, more prepared communities in Bengkulu Province and beyond.

BAREKENG JURNAL ILMU MATEMATIKA DAN TERAPANVol. 19(3)
Lampung University (ID), University of Bengkulu (ID)
Universitas Bengkulu
Openalex Percentile: Top 10%
Geochemistry and Geologic Mapping
2.48
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