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Pengaruh Indeks Massa Tubuh dan TrigliseridaTerhadap Gula Darah dengan Model Regresi Nonparametrik Spline Biprediktor

ESTIMASI: Journal of Statistics and Its Application · Vol. 2 No. 2 (2021) · pp. 71–79

DOI
10.20956/ejsa.v2i2.10262
ISSN
2721-379X, 2721-3803
Published
2021-07-23
Publisher
Hasanuddin University
Language
en

Abstract

The regression approach can be carried out using three approaches namely parametric, nonparametric and semiparametric approaches. Nonparametric regression is a statistical method used to see the relationship between the response variable and the predictor variable when the shape of the data curve is unknown. Diabetes mellitus (DM) or commonly called diabetes is a disease that is found and observed in various parts of the world today. DM is often marked by a significant increase in blood sugar levels. In this study using blood sugar levels as response variables, body mass index and triglycerides as predictor variables. Data were analyzed using truncated linear spline with one, two and three point knots experiments. The best model is obtained based on the minimum generalized cross validation (GCV) value. The results obtained that the best model is linear spline using three point knots.

Keywords

Collaboration network of the authors

40 authors · 105 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.

  • Sultan Ageng Tirtayasa University
  • Institut Agama Islam Negeri Kendari
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Nirwan IlyasAffiliation unknown4
Anisa AnisaSultan Ageng Tirtayasa University2
Sri Astuti ThamrinAffiliation unknown2
Anisa KalondengAffiliation unknown2
A.Muthiah Nur AngrianyAffiliation unknown2
Zhazha Alifkhamulki RamdhaniAffiliation unknown2
Samsul ArifinAffiliation unknown2
Nurtiti SunusiAffiliation unknown2
Andi Kresna JayaAffiliation unknown2
Muhammad FadilAffiliation unknown2
Widya Nauli Amalia PuteriAffiliation unknown1
Bunga ApriliaAffiliation unknown1
Andi Sitti Fahmi Riyanti HufainiAffiliation unknown1
Dwicahyo Ramadhan PriyatnaAffiliation unknown1
La Podje TalangkoAffiliation unknown1
Vieri KoerniawanAffiliation unknown1
Andi Tenri Riski AmaliaAffiliation unknown1
Muhammad Jayzul UsrahAffiliation unknown1
AnisaAffiliation unknown1
Novilia JaoAffiliation unknown1
Ainun Utari BudistiharahAffiliation unknown1
Mamik UtamiAffiliation unknown1
Sitti SahrimanAffiliation unknown1
Fitri AnnisaAffiliation unknown1
Fitri FitriAffiliation unknown1
Siswanto SiswantoAffiliation unknown1
Hajratul Ashwad KAffiliation unknown1
Andi Ummi Melin Aicha AichaAffiliation unknown1
Asnidar AsnidarAffiliation unknown1
Nurul HikmahInstitut Agama Islam Negeri Kendari1
Nasrah SirajangAffiliation unknown1
Fauziah NurhidayahAffiliation unknown1
Anni Ivoni ParapaAffiliation unknown1
Andi M Alfin BasoAffiliation unknown1
A. Elisha WulandariAffiliation unknown1
Belia Nurul FajriAffiliation unknown1
Abdullah PannuAffiliation 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/ESTIMASI/oai, first harvested 2 Nov 2026, last seen 2 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Pengaruh Indeks Massa Tubuh dan TrigliseridaTerhadap Gula Darah dengan Model Regresi Nonparametrik Spline Biprediktor</dc:title>
	<dc:creator xml:lang="en">Ente, Dewi Rahma</dc:creator>
	<dc:creator xml:lang="en">Islamiyati, Anna</dc:creator>
	<dc:creator xml:lang="en">Raupong, Raupong</dc:creator>
	<dc:subject xml:lang="en">Nonparametric regression</dc:subject>
	<dc:subject xml:lang="en">Spline truncated</dc:subject>
	<dc:subject xml:lang="en">Diabetes Mellitus</dc:subject>
	<dc:subject xml:lang="en">GCV</dc:subject>
	<dc:description xml:lang="en">The regression approach can be carried out using three approaches namely parametric, nonparametric and semiparametric approaches. Nonparametric regression is a statistical method used to see the relationship between the response variable and the predictor variable when the shape of the data curve is unknown. Diabetes mellitus (DM) or commonly called diabetes is a disease that is found and observed in various parts of the world today. DM is often marked by a significant increase in blood sugar levels. In this study using blood sugar levels as response variables, body mass index and triglycerides as predictor variables. Data were analyzed using truncated linear spline with one, two and three point knots experiments. The best model is obtained based on the minimum generalized cross validation (GCV) value. The results obtained that the best model is linear spline using three point knots.</dc:description>
	<dc:publisher xml:lang="en">Hasanuddin University</dc:publisher>
	<dc:date>2021-07-23</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/10262</dc:identifier>
	<dc:identifier>10.20956/ejsa.v2i2.10262</dc:identifier>
	<dc:source xml:lang="en">ESTIMASI: Journal of Statistics and Its Application; Vol. 2, No. 2, Juli, 2021 : Estimasi; 71-79</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/10262/7101</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2021 ESTIMASI: Journal of Statistics and Its Application</dc:rights>
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