Karangetang Mount Early Warning System using Inference Fuzzy Logic
Mount Karangetang, located on Siau Island, SITARO Archipelago Regency, is one of Indonesia’s 127 active volcanoes, making it the nation most susceptible to volcanic eruptions. In 2015, an eruption resulted in the displacement of as many as 465 residents, the destruction of four homes, and the loss o...
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Format: | Article |
Language: | English |
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EDP Sciences
2023-01-01
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Series: | E3S Web of Conferences |
Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/63/e3sconf_icobar23_01008.pdf |
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author | Saputro Immanuela Puspasari Kumenap Vivie Deyby Salindeho Megawati Sanger Junaidy Budi Adrian Angelia Melani |
author_facet | Saputro Immanuela Puspasari Kumenap Vivie Deyby Salindeho Megawati Sanger Junaidy Budi Adrian Angelia Melani |
author_sort | Saputro Immanuela Puspasari |
collection | DOAJ |
description | Mount Karangetang, located on Siau Island, SITARO Archipelago Regency, is one of Indonesia’s 127 active volcanoes, making it the nation most susceptible to volcanic eruptions. In 2015, an eruption resulted in the displacement of as many as 465 residents, the destruction of four homes, and the loss of gardens, animals, and property. In February of 2023, Mount Karangetang’s volcanic activity increased once more. This project seeks to aid the local Regional Disaster Management Agency in implementing preventative measures or evacuating residents; an early warning system for Mount Karangetang’s eruption will be created. Temperature and seismicity information will be collected through sensors deployed throughout the facility. In the meantime, the distance data is measured based on the real size of the residential location, and the height of the heated clouds is received from the observation post. The current study focuses on the development of a fuzzy logic model with four input variables and a single output variable with three levels: alert, alert, and alert. Depending on the status of the alert, the system can also emit repeated sirens for a specified length. In this study, 81 rules are utilized to determine the status of a warning. |
first_indexed | 2024-03-11T21:48:07Z |
format | Article |
id | doaj.art-f791717627fa43579a933980a883a004 |
institution | Directory Open Access Journal |
issn | 2267-1242 |
language | English |
last_indexed | 2024-03-11T21:48:07Z |
publishDate | 2023-01-01 |
publisher | EDP Sciences |
record_format | Article |
series | E3S Web of Conferences |
spelling | doaj.art-f791717627fa43579a933980a883a0042023-09-26T10:11:34ZengEDP SciencesE3S Web of Conferences2267-12422023-01-014260100810.1051/e3sconf/202342601008e3sconf_icobar23_01008Karangetang Mount Early Warning System using Inference Fuzzy LogicSaputro Immanuela Puspasari0Kumenap Vivie Deyby1Salindeho Megawati2Sanger Junaidy Budi3Adrian Angelia Melani4Computer Science Department, BINUS Online Learning, 11480 Bina Nusantara UniversityInformatics Engineering, Faculty of Engineering, 95000 Universitas Katolik De La SalleInformatics Engineering, Faculty of Engineering, 95000 Universitas Katolik De La SalleInformatics Engineering, Faculty of Engineering, 95000 Universitas Katolik De La SalleInformatics Engineering, Faculty of Engineering, 95000 Universitas Katolik De La SalleMount Karangetang, located on Siau Island, SITARO Archipelago Regency, is one of Indonesia’s 127 active volcanoes, making it the nation most susceptible to volcanic eruptions. In 2015, an eruption resulted in the displacement of as many as 465 residents, the destruction of four homes, and the loss of gardens, animals, and property. In February of 2023, Mount Karangetang’s volcanic activity increased once more. This project seeks to aid the local Regional Disaster Management Agency in implementing preventative measures or evacuating residents; an early warning system for Mount Karangetang’s eruption will be created. Temperature and seismicity information will be collected through sensors deployed throughout the facility. In the meantime, the distance data is measured based on the real size of the residential location, and the height of the heated clouds is received from the observation post. The current study focuses on the development of a fuzzy logic model with four input variables and a single output variable with three levels: alert, alert, and alert. Depending on the status of the alert, the system can also emit repeated sirens for a specified length. In this study, 81 rules are utilized to determine the status of a warning.https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/63/e3sconf_icobar23_01008.pdf |
spellingShingle | Saputro Immanuela Puspasari Kumenap Vivie Deyby Salindeho Megawati Sanger Junaidy Budi Adrian Angelia Melani Karangetang Mount Early Warning System using Inference Fuzzy Logic E3S Web of Conferences |
title | Karangetang Mount Early Warning System using Inference Fuzzy Logic |
title_full | Karangetang Mount Early Warning System using Inference Fuzzy Logic |
title_fullStr | Karangetang Mount Early Warning System using Inference Fuzzy Logic |
title_full_unstemmed | Karangetang Mount Early Warning System using Inference Fuzzy Logic |
title_short | Karangetang Mount Early Warning System using Inference Fuzzy Logic |
title_sort | karangetang mount early warning system using inference fuzzy logic |
url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/63/e3sconf_icobar23_01008.pdf |
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