Abstract
This research presented the ability of the Hilbert transformation of The Very Low Frequency-Electromagnetic (VLF-EM) data to investigate the presence of faults. VLF-EM data was collected in the Pinggirsari village area, Arjasari District, Bandung Regency, West Java, Indonesia. Through the Hilbert transformation, the VLF-EM data was converted into apparent resistivity data and then inverted into a resistivity cross-section. For comparison, qualitative interpretation was also conducted using both the Fraser and the Karous-Hjelt filters. Interpretation results using both the Fraser and Karous-Hjelt filters indicate the presence of faults through tilt-angle curve peaks and apparent current density anomalies. The resistivity cross-section resulting from the Occam inversion of the apparent resistivity data, derived from the Hilbert transformation, accurately delineated fault positions. Resistivity changes around 700-800 m indicated fault proximity to a depth of approximately 150 m, with a good match to the geological map. Within a distance of 0-700 m, low resistivity values were associated with the Malabar tuff, while >700 m, higher resistivity values were associated with the Waringin-Bedil andesite. The Hilbert transform helps in clarifying VLF data interpretation for precise fault detection through resistivity parameters.