| dc.description.abstract | Earthquakes are the sudden vibrations of the earth as a result of the simultaneous release of energy both on and on the earth's surface. The release of this energy causes seismic waves, and is destructive in nature. Earthquakes occur almost all the time on the entire surface of the earth. In order to simplify the process of identifying the arrival time of the arrival of waves, a Dynamic Time Warping algorithm is proposed for autopicking on earthquake data. This study develops a DTW algorithm based on the python programming language. This algorithm looks at the similarity of the patterns of the two data by making certain adjustments between the two data. By entering the input in the form of the arrival time of the wave arrival at a reference station, the information is used by the DTW algorithm to perform calculations and adjustments to other stations. The DTW algorithm on synthetic data was successfully used, and it was able to predict how far the data shifted, but if random noise was added there was a difference between the DTW results and the manual pick of 0.75 seconds. For real data use, the DTW algorithm is successfully used for picking the P wave on the Z component with the average value of the difference between Taupy, DTW and manual pick results of 1.2941 seconds, but it gives less than optimal results when picking the S wave on the N component and E with the average value difference between Taupy, DTW and manual pick results of 4.0544 seconds and 3.733 seconds. Suggestions for further studies include in-depth study of the DTW algorithm for picking other wave phases, the use of multi-references in the DTW algorithm and automation in the input of the DTW algorithm. All these suggestions need to be done to provide better results in future studies. | en_US |
