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Journal : Journal of Computer Science and Informatics Engineering (J-Cosine)

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.
Prototype Early Warning System Tanah Longsor Menggunakan Fuzzy Logic Berbasis Google Maps Sugianti, Novalia Dwirohmatun; Widiartha, Ida Bagus Ketut; Husodo, Ario Yudo
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 3 No 2 (2019): December 2019
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1108.717 KB) | DOI: 10.29303/jcosine.v3i2.273

Abstract

Landslide is one of frequent natural disaster in Indonesia that can cause many casualties, damage the buildings, loss of livelihoods, deteriorating sanitation, and the emergence of many diseases. To minimize this, prevention is needed by mapping the landslide prone areas and provided the early warning. This research will test in six areas in Lombok there are Batulayar, Bayan, Tanjung, Gangga, Sambelia, and Sembalun. The variable used are ground height, slope, rainfall, soil type, and land cover. There is a lot of method that can use to mapping such as fuzzy logic. Fuzzy logic is one of method that can mapping the input into the output space. By using fuzzy logic produces a level of accuracy for determining landslide prone areas is 83,3% and for the warning is 91,67%. So that, fuzzy logic can be used to mapping the landslide prone areas and make the early warning sytem.