Implementasi Wavelet pada Data Seismik Gunungapi - Dairoh Dairoh; Dega Surono Wibowo (Lambung Mangkurat University Press, 2020)
Noise decomposition on seismic volcanic data with wavelet using Daubechies wavelet decomposition on X and Y direction record data. Seismic volcanic data is in the form of broadband data, which broadband data has a wide frequency range so that it has a high enough noise level. So that when the noise decomposition process is carried out in selecting the decomposition of the noise it must be appropriate so that the information contained in it does not decompose, this is because the volcanic broadband seismic record data contains volcanic earthquake event information that has an amplitude at the same value as the amplitude of the noise. Therefore noise decomposition is done by implementing wavelet, that is by using Daubechies wavelet decomposition. The results show that Daubechies wavelet decomposition can break down noise properly without losing the information contained in the signal. The decomposition of noise uses Daubechies db 5 level 5 wavelet decomposition in detail. The results of the wavelet using wavelet decomposition obtained vulcanic earthquake events whose signal results showed conformity with volcanic earthquakes with T. Minakmi and wasserman's forms.