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All Journal Journal of Computer Science and Informatics Engineering (J-Cosine)
Topan Khrisnanda
Universitas Mataram
Computer Science & IT

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Expert System of Diagnosing Building Damage due to Earthquake using Backpropagation Artificial Neural Network Method Topan Khrisnanda; Ida Bagus Ketut Widiartha; I Gede Pasek Suta Wijaya
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 4 No 1 (2020): June 2020
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (472.865 KB) | DOI: 10.29303/jcosine.v4i1.302

Abstract

Earthquake is one of the most destructive natural disasters. After the earthquake, experts were deployed to survey the damage that occurred. One of the main objectives of the assessment task carried out by experts is to evaluate and classify buildings into several categories based on the level of damage that occurs. In this study, an expert system that could facilitate the assessment of building damage due to the earthquake was made using Backpropagation neural network method. The testing techniques used in this system are blackbox, accuracy and Mean Opinion Score (MOS) testing. MOS testing conducted by 30 respondents produced an MOS value of 4.54 from a scale of 5. While the average accuracy of the system obtained is 82.22% of the 30 case cases tested by 3 building damage experts.
Co-Authors I Gede Pasek Suta Wijaya Ida Bagus Ketut Widiartha