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REGRESSION NONPARAMETRIC SPLINE ESTIMATION ON BLOOD GLUCOSE OF INPATIENTS DIABETES MELLITUS AT SAMARINDA HOSPITAL

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 17 No. 1 (2023) · pp. 0147–0154

DOI
10.30598/barekengvol17iss1pp0147-0154
ISSN
2615-3017, 1978-7227
Published
2023-04-16
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

This study used a biresponse nonparametric regression method with truncated spline estimation that used two response variables. Nonparametric regression method is used when the regression curve is not known for its shape and pattern.One of the nonparametric regression model approaches that is often used is the spline. The truncated spline approach has a segmented polynomial function that provides flexibility. The data used in the study were blood glucose levels in patients with diabetes mellitus, cholesterol levels, and triglyceride levels in 2020. From the results of the study, the best nonparametric biresponse spline truncated regression model with three knot points has been obtained where the minimum GCV value is and has the an value of.

Collaboration network of the authors

34 authors · 73 co-authorship links

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Co-authorOrganisationJoint articles
Andrea Tri Rian DaniAffiliation unknown4
Surya PranggaAffiliation unknown3
Rizki Dwi FadlirhohimAffiliation unknown2
Zakiyah Mar'ahAffiliation unknown2
Meirinda FauziyahAffiliation unknown2
Eka Nur AmaliahAffiliation unknown1
Darnah DarnahAffiliation unknown1
Ahmad Rizky KesumaAffiliation unknown1
Farikah Ayu RinandaAffiliation unknown1
Ilyas AstafiraAffiliation unknown1
Nur AfrianiAffiliation unknown1
Tri Septi Ayu LestariAffiliation unknown1
Tirta PurnaragaAffiliation unknown1
Rifka Nurfaiza ZarkasiAffiliation unknown1
Aprianti Boma PadatuanAffiliation unknown1
Muhammad Danil PasarellaAffiliation unknown1
Fidia Deny Tisna AmijayaAffiliation unknown1
Memi Nor HayatiAffiliation unknown1
Yunda Sasha ParadillaAffiliation unknown1
Sitti AnggraeniAffiliation unknown1
Qonita Qurrota A'yunAffiliation unknown1
Frans Karta Sayoga SitohangAffiliation unknown1
Siti MahmudaAffiliation unknown1
Anggi Putri AnisarAffiliation unknown1
Marisa Nanda SaputriAffiliation unknown1
Wasono WasonoAffiliation unknown1
Rahmania RahmaniaAffiliation unknown1
Asnita AsnitaAffiliation unknown1
Indria SaskaAffiliation unknown1
Ghina Fadhilla MumtazAffiliation unknown1
Suyitno SuyitnoAffiliation 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) 
<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">REGRESSION NONPARAMETRIC SPLINE ESTIMATION ON  BLOOD GLUCOSE OF INPATIENTS DIABETES MELLITUS  AT SAMARINDA HOSPITAL</dc:title>
	<dc:creator>Sari, Ar Ruum Mia</dc:creator>
	<dc:creator>Sifriyani, Sifriyani</dc:creator>
	<dc:creator>Huda, Mohammad Nurul</dc:creator>
	<dc:description xml:lang="en-US">This study used a biresponse nonparametric regression method with truncated spline estimation that used two response variables. Nonparametric regression method is used when the regression curve is not known for its shape and pattern.One of the nonparametric regression model approaches that is often used is the spline. The truncated spline approach has a segmented polynomial function that provides flexibility. The data used in the study were blood glucose levels in patients with diabetes mellitus, cholesterol levels, and triglyceride levels in 2020. From the results of the study, the best nonparametric biresponse spline truncated regression model with three knot points has been obtained where the minimum GCV value is &amp;nbsp;and has the an &amp;nbsp;value of &amp;nbsp;.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2023-04-16</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/6771</dc:identifier>
	<dc:identifier>10.30598/barekengvol17iss1pp0147-0154</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications; 0147-0154</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol17iss1year2023</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/6771/5522</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 Ar Ruum Mia Sari, Sifriyani Sifriyani, Mohammad Nurul Huda</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>