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Modeling of COVID-19 Cases in Indonesia with the Method of Geographically Weighted Regression

Jurnal Matematika, Statistika dan Komputasi · Vol. 19 No. 2 (2023) · hlm. 342–350

DOI
10.20956/j.v19i2.23481
ISSN
2614-8811, 1858-1382
Terbit
2023-01-05
Penerbit
Department of Mathematics, Hasanuddin University
Bahasa
en
Lisensi
creativecommons.org/licenses/by/4.0

Abstrak

The COVID-19 pandemic has spread to all corners of the world, including Indonesia. Various factors affect the spread of COVID-19 cases in an area so that the government and the community can make prevention and control efforts so that this pandemic does not spread. This study aims to model the number of COVID-19 cases in Indonesia using the Geographically Weighted Regression (GWR) method, which develops a linear regression model. The GWR model uses weights based on the location of each observation so that the model is obtained for that location. Determine the weighting on the bandwidth. Optimum bandwidth selection is obtained by minimizing the value of Cross-Validation (CV). The GWR model using a fixed bisquare kernel weighting function has an optimum bandwidth of 0.999948 with a minimum CV value of 397.076.128 with a coefficient of determination R2 of 85.1 %. The results show that the number of positive cases positively correlates with the number of patients who died from COVID-19. In contrast, the number of recovered patients negatively correlates with the number of patients who died from COVID-19.

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  • Sultan Ageng Tirtayasa University
  • Universitas Halu Oleo
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Georgina Maria TinungkiAfiliasi tidak diketahui5
Nasrah SirajangAfiliasi tidak diketahui3
Nurtiti SunusiAfiliasi tidak diketahui3
Sitti SahrimanAfiliasi tidak diketahui2
Anisa AnisaSultan Ageng Tirtayasa University2
Saleh AFAfiliasi tidak diketahui2
Rizki AdiputraAfiliasi tidak diketahui1
Ika FitrianaAfiliasi tidak diketahui1
Ratmila MammiAfiliasi tidak diketahui1
Aqilah Salsabila RahmanAfiliasi tidak diketahui1
Riska RasyidAfiliasi tidak diketahui1
Nurhidaya LAfiliasi tidak diketahui1
Sonya SonyaAfiliasi tidak diketahui1
Rael Hofni TandirerungAfiliasi tidak diketahui1
Nuralyatussa’ adaAfiliasi tidak diketahui1
Alimatun NajihaAfiliasi tidak diketahui1
Andi Kresna JayaAfiliasi tidak diketahui1
Fadhila Febriyanti NajamuddinAfiliasi tidak diketahui1
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Agung Muhammad TakdirAfiliasi tidak diketahui1
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Aidawayati RangkutiAfiliasi tidak diketahui1
Andi waru A. PaluseriAfiliasi tidak diketahui1
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Irawaty IrawatyUniversitas Halu Oleo1
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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.unhas.ac.id/index.php/jmsk/oai, pertama di-harvest 5 Nov 2026, terakhir terlihat 5 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en">Modeling of COVID-19 Cases in Indonesia with the Method of Geographically Weighted Regression</dc:title>
	<dc:creator xml:lang="en">Arifin, Samsul </dc:creator>
	<dc:creator xml:lang="en">Herdiani, Erna Tri </dc:creator>
	<dc:subject xml:lang="en">Selected:COVID-19 Pandemic</dc:subject>
	<dc:subject xml:lang="en">Geographically Weighted Regression</dc:subject>
	<dc:subject xml:lang="en">Cross-Validation</dc:subject>
	<dc:subject xml:lang="en">Coefficient of Determination</dc:subject>
	<dc:description xml:lang="en">The COVID-19 pandemic has spread to all corners of the world, including Indonesia. Various factors affect the spread of COVID-19 cases in an area so that the government and the community can make prevention and control efforts so that this pandemic does not spread. This study aims to model the number of COVID-19 cases in Indonesia using the Geographically Weighted Regression (GWR) method, which develops a linear regression model. The GWR model uses weights based on the location of each observation so that the model is obtained for that location. Determine the weighting on the bandwidth. Optimum bandwidth selection is obtained by minimizing the value of Cross-Validation (CV). The GWR model using a fixed bisquare kernel weighting function has an optimum bandwidth of 0.999948 with a minimum CV value of 397.076.128 with a coefficient of determination R2   of 85.1 %. The results show that the number of positive cases positively correlates with the number of patients who died from COVID-19. In contrast, the number of recovered patients negatively correlates with the number of patients who died from COVID-19.</dc:description>
	<dc:publisher xml:lang="en">Department of Mathematics, Hasanuddin University</dc:publisher>
	<dc:date>2023-01-05</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/jmsk/article/view/23481</dc:identifier>
	<dc:identifier>10.20956/j.v19i2.23481</dc:identifier>
	<dc:source xml:lang="en">Jurnal Matematika, Statistika dan Komputasi; Vol. 19 No. 2 (2023): JANUARY 2023; 342-350</dc:source>
	<dc:source>2614-8811</dc:source>
	<dc:source>1858-1382</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/jmsk/article/view/23481/9157</dc:relation>
	<dc:relation>10.20956/j.v19i2.23481.g9157</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2023 Author and publisher</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
</oai_dc:dc>