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 ma...
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Universitas Pattimura
2025-07-01
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| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/15794 |
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| author | Baki Swita Mulia Astuti Fachri Faisal Aang Nuryaman |
| author_facet | Baki Swita Mulia Astuti Fachri Faisal Aang Nuryaman |
| author_sort | Baki Swita |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e2bd1f733d02488c8280636051572f46 |
| institution | Kabale University |
| issn | 1978-7227 2615-3017 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Universitas Pattimura |
| record_format | Article |
| series | Barekeng |
| spelling | doaj-art-e2bd1f733d02488c8280636051572f462025-08-20T03:41:56ZengUniversitas PattimuraBarekeng1978-72272615-30172025-07-011931537155210.30598/barekengvol19iss3pp1537-155215794MAPPING EARTHQUAKE MAGNITUDES IN BENGKULU PROVINCE AND SURROUNDING AREAS USING ROBUST ORDINARY KRIGINGBaki Swita0Mulia Astuti1Fachri Faisal2Aang Nuryaman3Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Bengkulu, IndonesiaDepartment of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Bengkulu, IndonesiaDepartment of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Bengkulu, IndonesiaDepartment of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Lampung, IndonesiaBengkulu 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.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/15794bengkulu provinceearthquake magnitude distributiongeostatisticsrobust ordinary krigingroot mean square error (rmse)semivariogram modeling |
| spellingShingle | Baki Swita Mulia Astuti Fachri Faisal Aang Nuryaman MAPPING EARTHQUAKE MAGNITUDES IN BENGKULU PROVINCE AND SURROUNDING AREAS USING ROBUST ORDINARY KRIGING Barekeng bengkulu province earthquake magnitude distribution geostatistics robust ordinary kriging root mean square error (rmse) semivariogram modeling |
| title | MAPPING EARTHQUAKE MAGNITUDES IN BENGKULU PROVINCE AND SURROUNDING AREAS USING ROBUST ORDINARY KRIGING |
| title_full | MAPPING EARTHQUAKE MAGNITUDES IN BENGKULU PROVINCE AND SURROUNDING AREAS USING ROBUST ORDINARY KRIGING |
| title_fullStr | MAPPING EARTHQUAKE MAGNITUDES IN BENGKULU PROVINCE AND SURROUNDING AREAS USING ROBUST ORDINARY KRIGING |
| title_full_unstemmed | MAPPING EARTHQUAKE MAGNITUDES IN BENGKULU PROVINCE AND SURROUNDING AREAS USING ROBUST ORDINARY KRIGING |
| title_short | MAPPING EARTHQUAKE MAGNITUDES IN BENGKULU PROVINCE AND SURROUNDING AREAS USING ROBUST ORDINARY KRIGING |
| title_sort | mapping earthquake magnitudes in bengkulu province and surrounding areas using robust ordinary kriging |
| topic | bengkulu province earthquake magnitude distribution geostatistics robust ordinary kriging root mean square error (rmse) semivariogram modeling |
| url | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/15794 |
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