Clustering Of Regions With Potential For A Tsunami In Indonesia Using The DBSCAN Method (Data Study for 1822 – 2022)

Abstract

Indonesia is a country comprising many islands and having an extensive coastline where coastal communities frequently engage in various activities. Tsunamis are a natural disaster risk in these coastal regions. This study aims to identify areas prone to tsunamis and analyze their characteristics using variables such as longitude, latitude, focal depth, and earthquake magnitude. The Density-Based Spatial Clustering of Application with Noise (DBSCAN) and OPTICS algorithms were used to group the tsunami datasets.