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COMPARING GAUSSIAN KERNEL AND QUADRATIC SPLINE OF NONPARAMETRIC REGRESSION IN MODELING INFECTIOUS DISEASES

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 17 No. 4 (2023) · pp. 2135–2146

DOI
10.30598/barekengvol17iss4pp2135-2146
ISSN
2615-3017, 1978-7227
Published
2023-12-19
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The regression curve for nonparametric regression is assumed to belong to some infinite-dimensional collection of functions, which allows great flexibility in the form of the curve. This research intends to compare the Gaussian Kernel and Quadratic Spline regressions in four infectious diseases in Indonesia by 2021. The data used is secondary data from the Central Bureau of Statistics and the Ministry of Health, Indonesia, and the sample consists of four infectious diseases in Indonesia by 2021 (Tuberculosis, Diarrhoeal, Pneumonia, and COVID-19). Considering the correlation value, it was found that the independent and dependent variables of the four infectious diseases are all highly correlated (r values are more than 0.7). Furthermore, the scatter plots for four infectious diseases do not follow a particular pattern; due to this, parametric regression cannot be used to analyze the data. Therefore, nonparametric regression was applied in this research. According to the analysis, the Gaussian Kernel is the best regression technique for modeling four infectious diseases in Indonesia by 2021, which its R2 values are 99.85% (Tuberculosis), 100% (Diarrhoeal), 99.91% (Pneumonia), and 99.99% (COVID-19).

Collaboration network of the authors

40 authors · 122 co-authorship links · showing the 40 most connected

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  • Universitas Halu Oleo
  • Institut Agama Islam Muhammadiyah Sinjai
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Agusyarif Rezka NuhaAffiliation unknown4
Nisky Imansyah YahyaAffiliation unknown3
Resmawan ResmawanAffiliation unknown3
Nurwan NurwanAffiliation unknown2
R. ResmawanAffiliation unknown2
Franky Alfrits OrohAffiliation unknown2
Asriadi AsriadiInstitut Agama Islam Muhammadiyah Sinjai2
Dewi Rahmawaty IsaAffiliation unknown2
Annisa Maharani BrahimAffiliation unknown2
Zulkifli AlamtahaAffiliation unknown1
Mohamad Rivaldi KoniAffiliation unknown1
N. NurwanAffiliation unknown1
Isran R. OliiAffiliation unknown1
Rahmayunda UsaliAffiliation unknown1
Nur Safitri AbdulAffiliation unknown1
Gusti Arviana RahmanUniversitas Halu Oleo1
Novianita AchmadAffiliation unknown1
Syarif AbdullahAffiliation unknown1
Sri Istiyarti Uswatun ChasanahAffiliation unknown1
Nina ValentikaAffiliation unknown1
La Ode SabranUniversitas Halu Oleo1
Ilham Dangu RianjayaAffiliation unknown1
Lilis Harianti HasibuanAffiliation unknown1
Sri Lestari MahmudAffiliation unknown1
Nazrilla Hasan LaitaAffiliation unknown1
Sri Endang SalehAffiliation unknown1
Debyyansa PakayaAffiliation unknown1
Irsan K. HasanAffiliation unknown1
Djihad WungguliAffiliation unknown1
Salmun K. NasibAffiliation unknown1
Jefri N. IsaAffiliation unknown1
Stella JunusAffiliation unknown1
Muftih Alwi AliuAffiliation 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://ojs3.unpatti.ac.id/index.php/barekeng/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">COMPARING GAUSSIAN KERNEL AND QUADRATIC SPLINE OF NONPARAMETRIC REGRESSION IN MODELING INFECTIOUS DISEASES</dc:title>
	<dc:creator>Adityaningrum, Amanda</dc:creator>
	<dc:creator>Ladjali, Sri Indriani</dc:creator>
	<dc:creator>Djakaria, Ismail</dc:creator>
	<dc:creator>Yahya, Lailany</dc:creator>
	<dc:creator>Payu, Muhammad Rezky Friesta</dc:creator>
	<dc:creator>Nashar, La Ode</dc:creator>
	<dc:creator>Jusuf, Herlina</dc:creator>
	<dc:description xml:lang="en-US">The regression curve for nonparametric regression is assumed to belong to some infinite-dimensional collection of functions, which allows great flexibility in the form of the curve. This research intends to compare the Gaussian Kernel and Quadratic Spline regressions in four infectious diseases in Indonesia by 2021. The data used is secondary data from the Central Bureau of Statistics and the Ministry of Health, Indonesia, and the sample consists of four infectious diseases in Indonesia by 2021 (Tuberculosis, Diarrhoeal, Pneumonia, and COVID-19). Considering the correlation value, it was found that the independent and dependent variables of the four infectious diseases are all highly correlated (r values are more than 0.7). Furthermore, the scatter plots for four infectious diseases do not follow a particular pattern; due to this, parametric regression cannot be used to analyze the data. Therefore, nonparametric regression was applied in this research . According to the analysis, the Gaussian Kernel is the best regression technique for modeling four infectious diseases in Indonesia by 2021, which its R2 values are 99.85% (Tuberculosis), 100% (Diarrhoeal), 99.91% (Pneumonia), and 99.99% (COVID-19).</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2023-12-19</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://ojs3.unpatti.ac.id/index.php/barekeng/article/view/9721</dc:identifier>
	<dc:identifier>10.30598/barekengvol17iss4pp2135-2146</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 17 No 4 (2023): BAREKENG: Journal of Mathematics and Its Applications; 2135-2146</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol17iss4year2023</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/9721/7198</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 Amanda Adityaningrum, Sri Indriani Ladjali, Ismail Djakaria, Lailany Yahya, Muhammad Rezky Friesta Payu, La Ode Nashar, Herlina Jusuf</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>