Analisis Potensi Kerusakan Akibat Gempa Menggunakan Metode Klasifikasi Bayesian

Awlad, Tanwiril (2021) Analisis Potensi Kerusakan Akibat Gempa Menggunakan Metode Klasifikasi Bayesian. Undergraduate thesis, Universitas Muhammadiyah Jember.

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Abstract

Indonesia is a country with a very high hazard potency. Indonesia has an average tectonic earthquake activity of 6,512 earthquakes per year, 543 earthquakes per month and 18 earthquakes per day. In terms of disaster prevention as described above, it can be done one way is to evaluate the problem is through statistical studies using Bayesian analysis. This study aims to analyze the application of bayesian classification method of earthquake impact in Indonesia and measure the accuracy, recall, and precision of the analysis of the most likely earthquake magnitude in Indonesia using bayesian classification method. The data obtained from BMKG website amounts to 140 data with five kinds of regions in Indonesia that have attributes of earthquake magnitude, earthquake depth, event time, earthquake area, and possible effects. After classifying, the result for Sumatra, Sulawesi, Java, and Nusa Tenggara is potential damage, while for Maluku region is potential damage and damage occurs. For the average accuracy obtained is 78.37394%, the recall value is 78.35334%, and the average precision value obtained is 66.56%.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: earthquake, potential damage, Bayesian classification method, accuracy, precision, recall
Subjects: 000 Computer Science, Information, & General Works > 004 Data Processing, Computer Science
Divisions: Faculty of Engineering > Department of Informatics Engineering (S1)
Department: S1 Teknik Informatika
Depositing User: Awlad Tanwiril
Contributors:
ContributionContributor NameNIDN/NIDK
Thesis advisorDaryanto, Daryantonidn0707077203
Thesis advisorOktavianto, Hardiannidn0722108105
Contact Email Address: tanwirilawlad@gmail.com
Date Deposited: 12 Jun 2021 01:22
Last Modified: 12 Jun 2021 01:27
URI: http://repository.unmuhjember.ac.id/id/eprint/10318

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