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Tsunami Impact Prediction System Based on TsunAWI Inundation Data

Journal of ICT Research and Applications (JICTRA) · Vol. 15 No. 1 (2021) · pp. 21–40

DOI
10.5614/itbj.ict.res.appl.2021.15.1.2
ISSN
2338-5499, 2337-5787
Published
2021-06-29
Publisher
DRI - ITB
Language
eng

Abstract

It is very important for tsunami early warning systems to provide inundation predictions within a short period of time. Inundation is one of the factors that directly cause destruction and damage from tsunamis. This research proposes a tsunami impact prediction system based on inundation data analysis. The inundation data used in this analysis were obtained from the tsunami modeling called TsunAWI. The inundation data analysis refers to the coastal forecast zones for each city/regency that are currently used in the Indonesia Tsunami Early Warning System (InaTEWS). The data analysis process comprises data collection, data transformation, data analysis (through GIS analysis, predictive analysis, and simple statistical analysis), and data integration, ultimately producing a pre-calculated inundation database for inundation prediction and tsunami impact prediction. As the outcome, the tsunami impact prediction system provides estimations of the flow depth and inundation distance for each city/regency incorporated into generated tsunami warning bulletins and impact predictions based on the Integrated Tsunami Intensity Scale (ITIS-2012). In addition, the system provides automatic sea level anomaly detection from tide gauge sensors by applying a tsunami detection algorithm. Finally, the contribution of this research is expected to bring enhancements to the tsunami warning products of InaTEWS.

Keywords

Collaboration network of the authors

10 authors · 15 co-authorship links · 4 across different organisations

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  • Bandung Institute of Technology
  • University of Singaperbangsa Karawang
  • Institut Teknologi Nasional Bandung
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Armein Z. R. LangiBandung Institute of Technology2
Carmadi MachbubBandung Institute of Technology1
Suhono Harso SupangkatBandung Institute of Technology1
Adhi RizalUniversity of Singaperbangsa Karawang1
Gladina DesideriaBandung Institute of Technology1
Rosa ElivianiBandung Institute of Technology1
Gina PurnamaBandung Institute of Technology1
Irma Amelia DewiInstitut Teknologi Nasional Bandung1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journals.itb.ac.id/index.php/jictra/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Tsunami Impact Prediction System Based on TsunAWI Inundation Data</dc:title>
	<dc:creator>Dermadi, Yedi</dc:creator>
	<dc:creator>Bandung, Yoanes</dc:creator>
	<dc:subject xml:lang="en-US">early warning system</dc:subject>
	<dc:subject xml:lang="en-US">inundation data analysis</dc:subject>
	<dc:subject xml:lang="en-US">tsunami impact prediction system</dc:subject>
	<dc:subject xml:lang="en-US">tsunami modeling</dc:subject>
	<dc:subject xml:lang="en-US">tsunami warning information</dc:subject>
	<dc:description xml:lang="en-US">It is very important for tsunami early warning systems to provide inundation predictions within a short period of time. Inundation is one of the factors that directly cause destruction and damage from tsunamis. This research proposes a tsunami impact prediction system based on inundation data analysis. The inundation data used in this analysis were obtained from the tsunami modeling called TsunAWI. The inundation data analysis refers to the coastal forecast zones for each city/regency that are currently used in the Indonesia Tsunami Early Warning System (InaTEWS). The data analysis process comprises data collection, data transformation, data analysis (through GIS analysis, predictive analysis, and simple statistical analysis), and data integration, ultimately producing a pre-calculated inundation database for inundation prediction and tsunami impact prediction. As the outcome, the tsunami impact prediction system provides estimations of the flow depth and inundation distance for each city/regency incorporated into generated tsunami warning bulletins and impact predictions based on the Integrated Tsunami Intensity Scale (ITIS-2012). In addition, the system provides automatic sea level anomaly detection from tide gauge sensors by applying a tsunami detection algorithm. Finally, the contribution of this research is expected to bring enhancements to the tsunami warning products of InaTEWS.</dc:description>
	<dc:publisher xml:lang="en-US">DRI - ITB</dc:publisher>
	<dc:date>2021-06-29</dc:date>
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	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
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	<dc:identifier>https://journals.itb.ac.id/index.php/jictra/article/view/14423</dc:identifier>
	<dc:identifier>10.5614/itbj.ict.res.appl.2021.15.1.2</dc:identifier>
	<dc:source xml:lang="en-US">Journal of ICT Research and Applications; Vol. 15 No. 1 (2021); 21-40</dc:source>
	<dc:source>2338-5499</dc:source>
	<dc:source>2337-5787</dc:source>
	<dc:source>10.5614/itbj.ict.res.appl.2021.15.1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journals.itb.ac.id/index.php/jictra/article/view/14423/5266</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2021 Journal of ICT Research and Applications</dc:rights>
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