Penerapan Datamining pada Data Gempa Bumi Terhadap Potensi Tsunami di Indonesia

Abstract

Indonesia is a maritime country that is located on 3 plates of the world or commonly called the Ring of Fire which causes frequent earthquakes. The earthquake is the biggest threat faced by the potential of the tsunami in it which can cause damage and even cause casualties. Data mining can explore pre-existing earthquake data and draw a pattern or conclusion from a database. The Naïve Bayes Classifier (NBC) algorithm is part of the data mining classification technique that is used to estimate or predict the chances of a possibility occurring. Based on the results and discussion, conclusions can be drawn by applying the Naïve Bayes Classifier (NBC) algorithm on earthquake data to potential tsunamis in Indonesia to find out the possible effects of earthquakes. With the testing data used the effect produced is the Potential Tsunami.