Melola Discovery

← Melola Discovery

Jurnal SINTA 2

Predicting Earthquake Magnitudes in Indonesia: Exploring the Potential of the Prophet Algorithm

Jurnal Ilmu Komputer dan Informasi (JIKI) · Vol. 17 No. 1 (2024) · pp. 77–87

DOI
10.21609/jiki.v17i1.1203
ISSN
2502-9274, 2088-7051
Published
2024-02-25
Publisher
Faculty of Computer Science - Universitas Indonesia
Language
eng

Abstract

Research on earthquakes has been extensively conducted by previous studies using various methods and specific discussions. Similarly, research to predict the magnitude of earthquakes that will occur in the future has also been conducted. This study employs the Prophet algorithm to test its capability in predicting a case study's magnitude using data with numerous missing values and outliers. The study is conducted without transformation and with Box-Cox and log-transformations. Transformations are applied to handle outliers. The results indicate that across the three experiments, the difference between the predicted and actual data ranges from 0.1 to 0.5 or even more. Performance metrics reveal that the log-transform is superior to the other two experiments, with a smaller MAE of 0.27 and a MAPE of 5.96%. Nevertheless, the use of the Prophet algorithm in this case study needs further investigation with different treatments to achieve more accurate results.

Collaboration network of the authors

3 authors · 3 co-authorship links

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Politeknik Harapan Bersama
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles

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://jiki.cs.ui.ac.id/index.php/jiki/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc)
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en-US">Predicting Earthquake Magnitudes in Indonesia: Exploring the Potential of the Prophet Algorithm</dc:title>
	<dc:creator>Nurindahsari, Susi </dc:creator>
	<dc:creator>Wiyono, Slamet</dc:creator>
	<dc:creator>Dairoh</dc:creator>
	<dc:description xml:lang="en-US">Research on earthquakes has been extensively conducted by previous studies using various methods and specific discussions. Similarly, research to predict the magnitude of earthquakes that will occur in the future has also been conducted. This study employs the Prophet algorithm to test its capability in predicting a case study's magnitude using data with numerous missing values and outliers. The study is conducted without transformation and with Box-Cox and log-transformations. Transformations are applied to handle outliers. The results indicate that across the three experiments, the difference between the predicted and actual data ranges from 0.1 to 0.5 or even more. Performance metrics reveal that the log-transform is superior to the other two experiments, with a smaller MAE of 0.27 and a MAPE of 5.96%. Nevertheless, the use of the Prophet algorithm in this case study needs further investigation with different treatments to achieve more accurate results.</dc:description>
	<dc:publisher xml:lang="en-US">Faculty of Computer Science  - Universitas Indonesia</dc:publisher>
	<dc:date>2024-02-25</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/1203</dc:identifier>
	<dc:identifier>10.21609/jiki.v17i1.1203</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Ilmu Komputer dan Informasi; Vol. 17 No. 1 (2024): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information); 77-87</dc:source>
	<dc:source>2502-9274</dc:source>
	<dc:source>2088-7051</dc:source>
	<dc:source>10.21609/jiki.v17i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/1203/504</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2024 Jurnal Ilmu Komputer dan Informasi</dc:rights>
</oai_dc:dc>