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Penggunaan Analisis Korespondensi Sederhana dalam Pemetaan Wilayah Potensi Bencana di Provinsi Sulawesi Tengah

ESTIMASI: Journal of Statistics and Its Application · Vol. 2 No. 1 (2021) · pp. 1–10

DOI
10.20956/ejsa.v2i1.10234
ISSN
2721-379X, 2721-3803
Published
2021-05-15
Publisher
Hasanuddin University
Language
en

Abstract

Disaster cases need to be analyzed considering that when a disaster occurs it will have an extraordinary impact. The statistical method that can be used to study disaster cases is a simple correspondence analysis. This study aims to map areas with the potential for natural disasters in the province of Central Sulawesi. So, in the analysis, regions are grouped according to row profile values that are greater than the average. The result of simple correspondence analysis obtained flood disaster has the potential to occur in Banggai, Morowali, Donggala, Buol, Parigi Moutong, Tojo Una-una, Sigi, and North Morowali. While the dominant tornado disaster occurred in Banggai Kepulauan, Banggai, Poso, Toli-toli, Parigi Moutong and Sigi. For regional landslides with potential Banggai Islands, Donggala, Toli-toli, Parigi Moutong, and Sigi. Then Banggai Islands and the City of Palu are the dominant regions for earthquake disasters. The results of the grouping can be the basis of government and community focus in tackling the dominant disasters occurring in their respective regions so as to minimize the impact when natural disasters occur.

Keywords

Collaboration network of the authors

40 authors · 109 co-authorship links · showing the 40 most connected

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

  • Hasanuddin University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Erna Tri HerdianiHasanuddin University9
Anisa AnisaHasanuddin University3
Nurtiti SunusiHasanuddin University3
RaupongAffiliation unknown2
Saleh AfAffiliation unknown2
Andi Kresna JayaHasanuddin University2
Nur Alfianingsih RajaHasanuddin University2
Anisa KalondengHasanuddin University2
Raupong RaupongHasanuddin University2
Suci Barlian SariHasanuddin University2
Ika FitrianaHasanuddin University1
Asti Inayati MagfirahAffiliation unknown1
Mega Selvia TjahayaAffiliation unknown1
Andi Isna YunitaHasanuddin University1
Reski AmalahAffiliation unknown1
Ratmila MammiAffiliation unknown1
Aqilah Salsabila RahmanAffiliation unknown1
Nurkamalia NurkamaliaAffiliation unknown1
Sitti SahrimanAffiliation unknown1
Mukrimin AdamAffiliation unknown1
Nurhidaya LAffiliation unknown1
Sitti SahrimanHasanuddin University1
Hendriete Tiur Marowi WaibusiHasanuddin University1
Anisa AnisaAffiliation unknown1
Victor LimanAffiliation unknown1
Sonya SonyaAffiliation unknown1
Surya Cahyadi SyamAffiliation unknown1
Nuralyatussa’ AdaAffiliation unknown1
Nurul HikmahAffiliation unknown1
Parida Ayu NingsiAffiliation unknown1
Muhammad ZakirHasanuddin University1
Anna IslamiyatiHasanuddin University1
Muhammad Jayzul UsrahHasanuddin University1
Ummi SariHasanuddin University1
Fajar AffanHasanuddin University1
Alimatun NajihaHasanuddin University1
Taufiq AkbarHasanuddin University1

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://journal.unhas.ac.id/index.php/ESTIMASI/oai, first harvested 2 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Penggunaan Analisis Korespondensi Sederhana dalam Pemetaan Wilayah Potensi Bencana di Provinsi Sulawesi Tengah</dc:title>
	<dc:creator xml:lang="en">Kasih, Iis Cendrah</dc:creator>
	<dc:creator xml:lang="en">Tinungki, Georgina Maria</dc:creator>
	<dc:creator xml:lang="en">Sirajang, Nasrah</dc:creator>
	<dc:subject xml:lang="en">Central Sulawesi</dc:subject>
	<dc:subject xml:lang="en">Natural Disaster</dc:subject>
	<dc:subject xml:lang="en">Row of Profile</dc:subject>
	<dc:subject xml:lang="en">Simple Correspondence Analysis.</dc:subject>
	<dc:description xml:lang="en">Disaster cases need to be analyzed considering that when a disaster occurs it will have an extraordinary impact. The statistical method that can be used to study disaster cases is a simple correspondence analysis. This study aims to map areas with the potential for natural disasters in the province of Central Sulawesi. So, in the analysis, regions are grouped according to row profile values that are greater than the average. The result of simple correspondence analysis obtained flood disaster has the potential to occur in Banggai, Morowali, Donggala, Buol, Parigi Moutong, Tojo Una-una, Sigi, and North Morowali. While the dominant tornado disaster occurred in Banggai Kepulauan, Banggai, Poso, Toli-toli, Parigi Moutong and Sigi. For regional landslides with potential Banggai Islands, Donggala, Toli-toli, Parigi Moutong, and Sigi. Then Banggai Islands and the City of Palu are the dominant regions for earthquake disasters. The results of the grouping can be the basis of government and community focus in tackling the dominant disasters occurring in their respective regions so as to minimize the impact when natural disasters occur.</dc:description>
	<dc:publisher xml:lang="en">Hasanuddin University</dc:publisher>
	<dc:date>2021-05-15</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://journal.unhas.ac.id/index.php/ESTIMASI/article/view/10234</dc:identifier>
	<dc:identifier>10.20956/ejsa.v2i1.10234</dc:identifier>
	<dc:source xml:lang="en">ESTIMASI: Journal of Statistics and Its Application; Vol. 2, No. 1, Januari, 2021 : Estimasi; 1-10</dc:source>
	<dc:source>2721-379X</dc:source>
	<dc:source>2721-3803</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/ESTIMASI/article/view/10234/6793</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2020 ESTIMASI: Journal of Statistics and Its Application</dc:rights>
</oai_dc:dc>