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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

Link: https://ifory.id/abstract/qBX3ru6TULnC

Conference: The 1st Annual Advanced Technology, Applied Science, and Engineering Conference (ATASEC 2019)

Plain Format | Corresponding Author (Ratih Indri Hapsari)

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