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MENGOPTIMALKAN PETA KERAWANAN LONGSOR LAHAN PADA ANALISIS REGRESI LOGISTIK DENGAN PENDETAILAN PETA GEOLOGI DI DAERAH ALIRAN SUNGAI KLADEN, KABUPATEN REMBANG, JAWA TENGAH: Optimizing Landslide Susceptibility Map on Logistic Regression Model with Detailed Geological Map in the Kladen Watershed, Rembang Regency, Jawa Tengah

Jurnal Ecosolum · Vol. 11 No. 1 (2022) · pp. 57–80

DOI
10.20956/ecosolum.v11i1.19566
ISSN
2654-430X, 2252-7923
Published
2022-07-17
Publisher
Universitas Hasanuddin
Language
en
License
creativecommons.org/licenses/by-nc/4.0

Abstract

Landslides are common problems in watershed management due to their social and economic impacts. Landslide susceptibility mapping is needed to identify areas that need priority in the mitigation program. In landslide susceptibility mapping, the most commonly used geological map is regional map, which is not suited for small to medium-sized areas such as the Kladen watershed, in Rembang, Central Java. This study aims to improve the available geological map with a more detailed lithological unit than regional geological maps, and produce susceptibility maps using geological, geomorphological, and land cover variables. A comparison was performed between the results obtained with the regional geological map and the improved geological map. The logistic regression was selected as it has provided high accuracy for landslide hazard analysis, and does not depend on the subjectivity of the researcher. The results of the landslide susceptibility analysis with regional geological maps show that the lithological factor is statistically insignificant, while in the analysis with a more detailed geological map, it was significant and has higher relevancy than the geomorphology and land cover. The predictive performance test of both models with the area under the curve method shows that the improvement of the geological map increases the performance value from 0,704 to 0,782, producing more reliable landslide susceptibilty map.

Keywords

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Ahmad Fauzan AdzimaAffiliation unknown1
Muhammad Anggri SetiawanAffiliation unknown1

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/ecosolum/oai, first harvested 2 Nov 2026, last seen 2 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">MENGOPTIMALKAN PETA KERAWANAN LONGSOR LAHAN PADA ANALISIS REGRESI LOGISTIK DENGAN PENDETAILAN PETA GEOLOGI DI DAERAH ALIRAN SUNGAI KLADEN, KABUPATEN REMBANG, JAWA TENGAH: Optimizing Landslide Susceptibility Map on Logistic Regression Model with Detailed Geological Map in the Kladen Watershed, Rembang Regency, Jawa Tengah</dc:title>
	<dc:creator xml:lang="en">Aditya, Hafiz Fatah Nur</dc:creator>
	<dc:creator xml:lang="en">Samodra, Guruh</dc:creator>
	<dc:creator xml:lang="en">Mardiatno, Djati</dc:creator>
	<dc:subject xml:lang="en">lanslides</dc:subject>
	<dc:subject xml:lang="en">lithology</dc:subject>
	<dc:subject xml:lang="en">logistic regression</dc:subject>
	<dc:subject xml:lang="en">susceptibility</dc:subject>
	<dc:description xml:lang="en">Landslides are common problems in watershed management due to their social and economic impacts. Landslide susceptibility mapping is needed to identify areas that need priority in the mitigation program. In landslide susceptibility mapping, the most commonly used geological map is regional map, which is not suited for small to medium-sized areas such as the Kladen watershed, in Rembang, Central Java. This study aims to improve the available geological map with a more detailed lithological unit than regional geological maps, and produce susceptibility maps using geological, geomorphological, and land cover variables. A comparison was performed between the results obtained with the regional geological map and the improved geological map. The logistic regression was selected as it has provided high accuracy for landslide hazard analysis, and does not depend on the subjectivity of the researcher. The results of the landslide susceptibility analysis with regional geological maps show that the lithological factor is statistically insignificant, while in the analysis with a more detailed geological map, it was significant and has higher relevancy than the geomorphology and land cover. The predictive performance test of both models with the area under the curve method shows that the improvement of the geological map increases the performance value from 0,704 to 0,782, producing more reliable landslide susceptibilty map.</dc:description>
	<dc:publisher xml:lang="en">Universitas Hasanuddin</dc:publisher>
	<dc:date>2022-07-17</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unhas.ac.id/index.php/ecosolum/article/view/19566</dc:identifier>
	<dc:identifier>10.20956/ecosolum.v11i1.19566</dc:identifier>
	<dc:source xml:lang="en">Jurnal Ecosolum; Vol. 11 No. 1 (2022): JUNI; 57-80</dc:source>
	<dc:source>2654-430X</dc:source>
	<dc:source>2252-7923</dc:source>
	<dc:source>10.20956/ecosolum.v11i1</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/ecosolum/article/view/19566/8438</dc:relation>
	<dc:rights xml:lang="en">http://creativecommons.org/licenses/by-nc/4.0</dc:rights>
</oai_dc:dc>