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@article{J.Gauss29499, author = {Denny Manalu and Rita Rahmawati and Tatik Widiharih}, title = {PENGELOMPOKAN TITIK GEMPA DI PULAU SULAWESI MENGGUNAKAN ALGORITMA ST-DBSCAN (Spatio Temporal-Density Based Spatial Clustering Application with Noise)}, journal = {Jurnal Gaussian}, volume = {10}, number = {4}, year = {2021}, keywords = {Data mining, earthquake, clustering, spatio-temporal, ST-DBSCAN}, abstract = { Earthquake is a natural disaster which is quite serious in Indonesia, especially on Sulawesi Island. Earthquake is fearful because it can’t be predicted when it will come, where it will come, and how strong the vibration, that often causes fatal damage and casualties. In effort to minimize losses caused by earthquake, it is necessary to divide areas which are easily affected by earthquake. One of the methods that can be used in dividing the area is by using the clustering technique. This research by using a clustering method with the ST-DBSCAN (Spatial Temporal-Density Based Spatial Clustering Application with Noise) algorithm on dataset of earthquake points in Sulawesi Island in 2019. This method by using the spatial distance parameters (Eps1 = 0.45), the temporal distance parameters (Eps2 = 7), and minimum number of cluster members (MinPts = 4), resulting in a total of 60 clusters with 8 large clusters and 216 noises }, issn = {2339-2541}, pages = {554--561} doi = {10.14710/j.gauss.10.4.554-561}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/29499} }
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