System for Estimating Lahar Disaster Status using Machine Learning Method
Ratih Indri Hapsari1*), Bima Ahida Indaka Sugna2), ErfanRohadi2), and Rosa Andrie Asmara2)
1) Department of Civil Engineering, State Polytechnic of Malang
2) Department of Informatics Technology, State Polytechnic of Malang
*) ratih[at]polinema.ac.id
Abstract
Lahar disaster is a debris flow event following volcanic eruption that is triggered by intense rainfall. This disaster induces a potential losses that include casualty, damage or loss of property, and environmental disruption. In this study the system of lahar vulnerability assessment is developed. The target area is a river is Merapi volcano Indonesia. Naive Bayes Classifier Method is applied to classify areas or flood-prone zones or safe. In this study, the database and the interface is created using MySQL and PHP Hypertext Preprocessor. The determining factors are spatially distributed rainfall intensity from X-band weather radar, topographical factor, and soil type. This research has produced a flood disaster status determination system on the slopes of Merapi with an accuracy rate of 84.6%, from the results of taking 10% of the training data. The output of this system is an information system shown in vulnerability map that provides information about the status of susceptible zones to lahar flow.
Keywords: Lahar, Naive Bayes Classifier, Merapi Volcano
Topic: Civil Engineering