Many scientific studies has detected ULF (ultra-low frequency) emission before an earthquake. An earlier study of Loma Prieta 7.1 M earthquake in 1989 shows ULF anomaly ranged between 0.01-10 Hz before an earthquake. A similar study of Kushiro earthquake 6.4 Mw shows that the ULF anomaly can be detected at a frequency range of 0.022-0.1 Hz. Furthermore, a study conducted in Sumatra Island from 2007-2012 shows the ULF anomaly at 0.01-0.06 Hz. Newer study on the 2009 Padang earthquake and Mentawai 2010 earthquake shows ULF emission between 0.012-0.022 Hz. Based on the aforementioned researches, a study is conducted on frequency range of 0.01-0.09 Hz to identify the optimum ULF frequency. Study conducted in this case uses magnetic diurnal variation data from Sumatra region from 2017 to 2018, especially earthquakes recorded at Gunung Sitoli (GSI), and Sicincin (SCI) stations. Previous studies above provide an overview of ULF ranges associated with earthquakes. Based on all above, an analysis is conducted to find the precursors using data of past earthquake events by utilizing Fast Fourier Transform to transform time-domain data to frequency domain, bandpass filters to eliminate noise, power ratio of Z/H to determine the time window, and Single Station Transfer Function to determine the location window. Lastly, moving average is used to assist determination of time window. Magnetic anomalies between 0.01-0.03 Hz, with amplitude exceeding monthly average, were observed before the earthquakes. Analysis in this frequency range shows occurence of earthquake 5-6 days after geomagnetic anomalies were detected. This study shows that location window prediction is possible with 100% accuracy. Therefore, 0.01-0.03 is currently the optimum frequency for precursor analysis.
|Journal||IOP Conference Series: Earth and Environmental Science|
|Publication status||Published - 30 Dec 2019|
|Event||2nd International Conference on Life and Applied Sciences for Sustainable Rural Development, ICLAS-SURE 2019 - Purwokerto, Indonesia|
Duration: 20 Nov 2019 → 22 Nov 2019