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Abstrak :
Penelitian ini menginvestigasi struktur kecepatan S di Lautan Hindia melalui fitting seismogram, akibat gempa C081499A, Sumatra Selatan dan direkam di stasiun RER, Pulau Reunion, Perancis. seismogram observasi dibandingkan dengan seismogram sintetik dalam domain waktu dan ketiga komponen kartesian secara simultan. Seismogram sintetik dihitung dengan program GEMINI, dimana input awalnya adalah model bumi global Ocean dan PREMAN. Selain itu pada kedua seismogram dikenakan low-pass filter dengan frekuensi corner pada 20 mHz. Analisis seismogram menunjukkan penyimpangan yang sangat kuat pada pengamatan atas waktu tiba, jumlah osilasi dan tinggi amplitudo, pada gelombang permukaan Love dan Rayleigh dan gelombang ruang S. Untuk menyelesaikan simpangan yang dijumpai diperlukan koreksi atas struktur bumi meliputi ketebalan kulit bumi, gradien kecepatan βh dan besar koefisien-koefisien untuk βh dan βv di upper mantle, dan sedikit perubahan pada kecepatan S di lapisan-lapisan bumi hingga kedalaman 400 km. Fitting seismogram diperoleh dengan baik pada waveform fase gelombang, baik waktu tempuh osilasi utama dan jumlah osilasi. Hasil riset ini menunjukkan, bahwa daerah Lautan Hindia mempunyai koreksi atas struktur kecepatan S dengan nilai positif terhadap model lautan. Hasil ini berbeda dengan hasil riset seismologi lainnya.

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The research investigated the S speed of earth structure under Indian Ocean using seismogram fitting, due to the C081499A earthquake, South Sumatra and recorded in the observation station RER at Reunion Island, France. The observed seismogram is compared to its synthetic in time domain and three cartension components simultaneously. Synthetic seismogram is calculated with the GEMINI program, the initial inputs are the global earth models of Ocean and PREMAN. Prior to seismogram comparison, a low-pass filter with corner frequency of 20 mHz is imposed. The result of analysis shows a very strong deviation at the arrival time, oscillation amount and amplitude height of Love and Rayleigh surface waves and S body wave. To overcome the found discrepancies a correction to the earth structure is needed covering the earth crust thickness, speed gradient of βh and zero-order coefficient for the βh and βv in upper mantle, and a little change in S speed in earth layers down to a depth of 400 km. Seismogram fitting is better obtained at waveform of the wave phase, either the travel time or oscillation number of S wave and Love surface wave. The results shows that the Indian Ocean has correction to the S speed structure, which is positive to standard earth model. This result differs from other seismology research.

Abstrak :
In this research the model of earth layers between earthquake's epicenter in Hokkaido Japan and observation station in Black Forest of Observatory (BFO), Germany is investigated. The earth model is 1-D that represents the average speed model. The earth model is obtained by seismogram comparison between data and synthetic seismogram in time domain and three components simultaneously. Synthetic Seismogram is calculated with the Green's function of the Earth by MINor Integration (GEMINI) program, where program's input is initially the earth model IASPEI91, PREMAN and also the Centroid Moment Tensor (CMT) solution of the earthquake. A Butterworth low-pass filter with corner frequency of 20 mHz is imposed to measured and synthetic seismogram. On seismogram comparison we can find unsystematic discrepancies, covering the travel time and waveform of all wave phases, namely on P, S, SS wave and surface wave of Rayleigh and Love. Solution to the above mentioned discrepancies needs correction to the earth structure, that covering the change of earth crust thickness, the gradient of �?�h and value of zero order coefficient in �?�h and �?�v in upper mantle, to get the fitting on the surface wave of Love and Rayleigh. Further correction to accomplish the discrepancies on body waves is conducted on layers beneath upper mantle down to depth of 630 km, where a little change at speed model of P and S wave is carried out. The number of oscillation amount especially on Love wave is influenced by earth crust depth earth. Good fitting is obtained at phase and amplitude of Love wave, but also at amplitude of some body wave too. This effect is not yet been exploited for the determination of moment tensor.

Abstrak :
Gempabumi yang terjadi akibat pelepasan energi di dalam permukaan bumi akan menghasilkan penjalaran gelombang seismik. Gelombang tersebut akan terekam oleh stasiun penerima yang nantinya dilakukan pemrosesan data sebagai kebutuhan interpretasi dari seismogram. Pada proses pengolahan data salah satunya yaitu penentuan waktu tiba gelombang. Penentuan waktu tiba dari gelombang primer dan sekunder masih dilakukan dengan cara manual oleh operator sehingga memiliki kekurangan seperti waktu yang lama, tingkat subjektivitas yang tinggi dan hasil akurasi yang rendah. Pada penelitian ini dilakukan inovasi dalam penentuan arrival time dengan pendekatan deep learning yaitu menggunakan algoritma Convolutional Neural Network (CNN) dan Long Short Term Memory (LSTM). Program yang dibuat dengan menerapkan kedua algoritma ini akan dilakukan pengujian terhadap data lain. Hasil uji pada program yang sudah dibuat kemudian dilakukan komparasi pada hasil picking dari IRIS Wilber. Uji yang dilakukan menggunakan data dari gempa Palu 28 September 2018. Hasil uji dari program komputer yang dibuat dengan perbandingan picking hasil IRIS Wilber memberikan rata-rata eror sekitar 0.005 dan komparasi waktu dari origin time memiliki perbedaan sekitar 2 detik. Program ini sudah menghasilkan hasil prediksi yang cukup akurat. ......Earthquakes that occur due to the release of energy in the earth's surface will result in the propagation of seismic waves. These waves will be recorded by the receiving station which will later be processed as a result of the interpretation of the seismogram. One of the data processing processes is determining the arrival time of the waves. The determination of the arrival time of the primary and secondary waves is still done manually by the operator so that it has drawbacks such as a long time, a high degree of subjectivity and low accuracy. In this study, innovation was carried out in determining arrival time with a deep learning approach, namely using the Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) algorithms. Programs created by applying these two algorithms will be tested on other data. The test results on the program that has been made are then compared to the picking results from IRIS Wilber. The test was carried out using data from the Palu earthquake on 28 September 2018. The test results from a computer program made with a comparison of IRIS Wilber's picking results give an average error of around 0.005 and a comparison of the time from the origin time has a difference of about 2 seconds. This program has produced predictive results that are quite accurate.

Abstrak :
In this research the S speed structure is investigated by seismogram analysis of Washington's earthquake, C022801L using data of TUC station, Tucson, Arizona, U.S.A. The seismogram comparison between the observed and the synthetic seismogram is conducted in time domain and three components simultaneously. The initially input for the calculation of synthetic seismogram is earth model of PREMAN and CMT solution from the earthquake. A low-pass Butterworth filter with corner frequency of 20 mHz is convolved to observed and synthetic seismogram. Waveform comparison shows a real deviation when travel time and waveform of some wave phase are compared, namely on S wave, surface wave of Love and Rayleigh and wave ScS and ScS-2. This research shows, how sensitive the waveform is to the earth model, better than the method of travel time or the dispersion analysis. Research hereinafter is addressed to finish the found discrepancies at S wave, surface wave of Love and Rayleigh and ScS and ScS-2 wave, in observation station TUC. To obtain the seismogram fitting, correction for S speed structure in earth model is needed, that are changes of earth crust thickness, the speed model of  in upper mantle covering the speed gradient of h and value of zeroeth order coefficient for the h and v, for accomplishing the discrepancies at surface wave of Love and Rayleigh. Further correction on S speed is conducted to accomplish the deviation at S wave at earth layering systems from Upper Mantle up to a 630 km depth. Mean while for the ScS and ScS-2 wave phase the correction is carried out on S speed in the earth layers up to CMB. Fitting Seismogram is obtained at waveform of various wave phases that is S wave, surface wave of Love and Rayleigh and ScS, ScS-2 wave, either on travel time or especially also at oscillation number in Love wave. This result indicates that the anisotropy is occurred not only in upper mantle but till deeper earth layers, till CMB.

Abstrak :
Dalam rangka memperluas analisis telah dikaji basil perekaman seismogram permukaan tanah yang berasal dari sumber getaran mesin pabrik semen PT Semen Nusantara, Cilacap, Jawa Tengah. Dalam hal ini kajian yang akan dilakukan adalah evaluasi amplitudo kecepatan, pergeseran dan percepatan getaran permukaan tanah pada beberapa frekuensi dan kajian mengenai polarisasi getaran permukaan tanah. Hasil penelitian ini selain untuk memperkaya khasanah penelitian dalam bidang Geofisika Lingkungan, akan memberikan gambaran yang nyata tentang mutu lingkungan kita yang berkaitan dengan getaran permukaan tanah yang disebabkan oleh sumber getaran mesin pabrik.