Arif Ismul Hadi
Geophysics Study Program, Department of Physics, FMIPA, Universitas Bengkulu, Jl. W.R. Supratman, Kandang Limun, Bengkulu 38371, Bengkulu Province, Indonesia

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Analysis of ULF Geomagnetic Anomalies as Earthquake Precursor Indicators in Bengkulu Dama Rahma Sagita; Arif Ismul Hadi; Detalia Nurutami
Journal of Technomaterial Physics Vol. 8 No. 2 (2026): Journal of Technomaterial Physics
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jotp.v8i2.25750

Abstract

Earthquake prediction remains an unresolved scientific challenge, motivating extensive efforts to identify physical phenomena that can serve as reliable precursors to seismic events. This study investigates Ultra Low Frequency (ULF) geomagnetic signal anomalies using the ratio of the vertical to horizontal geomagnetic field components (Z/H) as potential earthquake precursor indicators. In addition, the relationship between anomaly amplitude and earthquake characteristics is evaluated. The analysis utilizes geomagnetic H and Z component data recorded at the Kepahiang Geomagnetic Station (KPY), earthquake events with magnitudes greater than 4.5 that occurred in Bengkulu Province between May and December 2022, and the Disturbance Storm Time (Dst) index to distinguish seismogenic anomalies from geomagnetic storm effects. ULF anomalies were identified using the moving average and standard deviation of the Z/H ratio, followed by lead-time analysis, Dst-based validation, and linear regression to examine the relationship between anomaly amplitude and earthquake magnitude. The results show that most earthquake events were preceded by detectable ULF anomalies occurring 3–25 days before the mainshock. Furthermore, a positive linear relationship was observed between the Z/H anomaly amplitude and earthquake magnitude, although the correlation strength was relatively weak. These findings suggest that ULF geomagnetic anomalies derived from the Z/H ratio have potential as earthquake precursor indicators in Bengkulu Province, while further studies using longer observation periods and larger datasets are required to improve their reliability and predictive capability.