Melola Discovery

← Melola Discovery

Jurnal

Estimasi Model Regresi Kuantil Spline Kuadratik pada Data Trombosit dan Hematokrit Pasien DBD

ESTIMASI: Journal of Statistics and Its Application · Vol. 1 No. 2 (2022) · pp. 58–64

DOI
10.20956/ejsa.v1i2.9264
ISSN
2721-379X, 2721-3803
Published
2022-02-02
Publisher
Hasanuddin University
Language
en

Abstract

Nonparametric quantile regression is used to estimate the regression function when assumptions about the shape of the regression curve are unknown. It is only assumed to be subtle by involving quantile values. One estimator in nonparametric regression is spline. The segmented properties of the spline provide more flexibility than ordinary polynomials. Therefore, the nature of the spline makes it possible to adapt more effectively to the local characteristics of a function or data. This study proposes to get the results of the estimation platelet count model to the hematocrit value of DHF. The optimal model obtained from the estimation of quadratic spline quantile regression is at quantile 0.5 with one knot and the GCV value is 41.5. The results of the estimation show that there is a decrease in platelet counts as the percentage of hematocrit increase.

Keywords

Collaboration network of the authors

40 authors · 88 co-authorship links · 5 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Islam Negeri Raden Fatah Palembang
  • Sultan Ageng Tirtayasa University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Raupong RaupongAffiliation unknown6
Andi Kresna JayaAffiliation unknown4
Anisa KalondengAffiliation unknown4
Sri Astuti ThamrinAffiliation unknown2
Widya Nauli Amalia PuteriAffiliation unknown2
Nurtiti SunusiAffiliation unknown2
Muhammad FadilAffiliation unknown2
Siswanto SiswantoAffiliation unknown2
Deby NovianiUniversitas Islam Negeri Raden Fatah Palembang1
Winda Rahayu FitrianiUniversitas Islam Negeri Raden Fatah Palembang1
Cinta MellindaUniversitas Islam Negeri Raden Fatah Palembang1
Feni JuniatiUniversitas Islam Negeri Raden Fatah Palembang1
Muhammad Win AfganiUniversitas Islam Negeri Raden Fatah Palembang1
Heni PujiastutiSultan Ageng Tirtayasa University1
Hepsi NindiasariSultan Ageng Tirtayasa University1
Zhazha Alifkhamulki RamdhaniAffiliation unknown1
Samsul ArifinAffiliation unknown1
Andi Sitti Fahmi Riyanti HufainiAffiliation unknown1
Grace Oktavia YusufAffiliation unknown1
Dewi Rahma EnteAffiliation unknown1
Azman AzmanAffiliation unknown1
Muhammad Jayzul UsrahAffiliation unknown1
AnisaAffiliation unknown1
Novilia JaoAffiliation unknown1
Najiha AlimatunAffiliation unknown1
Ainun Utari BudistiharahAffiliation unknown1
Mamik UtamiAffiliation unknown1
Fitri FitriAffiliation unknown1
Nurul IkhsaniAffiliation unknown1
Hajratul Ashwad KAffiliation unknown1
Andi Ummi Melin Aicha AichaAffiliation unknown1
Georgina Maria TinungkiAffiliation unknown1
Victor LimanAffiliation unknown1
Asnidar AsnidarAffiliation unknown1
Wa Ode Sitti Amni AmniAffiliation unknown1
Kevin Ekarinaldo PalunganAffiliation 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) 
<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">Estimasi Model Regresi Kuantil Spline Kuadratik pada Data Trombosit dan Hematokrit Pasien DBD</dc:title>
	<dc:creator xml:lang="en">Aprilia, Bunga</dc:creator>
	<dc:creator xml:lang="en">Islamiyati, Anna</dc:creator>
	<dc:creator xml:lang="en">Anisa, Anisa</dc:creator>
	<dc:creator xml:lang="en">Ilyas, Nirwan</dc:creator>
	<dc:subject xml:lang="en">Hematocrit</dc:subject>
	<dc:subject xml:lang="en">Quantile</dc:subject>
	<dc:subject xml:lang="en">Quadratic</dc:subject>
	<dc:subject xml:lang="en">Spline</dc:subject>
	<dc:subject xml:lang="en">Platelet</dc:subject>
	<dc:description xml:lang="en">Nonparametric quantile regression is used to estimate the regression function when assumptions about the shape of the regression curve are unknown. It is only assumed to be subtle by involving quantile values. One estimator in nonparametric regression is spline. The segmented properties of the spline provide more flexibility than ordinary polynomials. Therefore, the nature of the spline makes it possible to adapt more effectively to the local characteristics of a function or data. This study proposes to get the results of the estimation platelet count model to the hematocrit value of DHF. The optimal model obtained from the estimation of quadratic spline quantile regression is at quantile 0.5 with one knot and the GCV value is 41.5. The results of the estimation show that there is a decrease in platelet counts as the percentage of hematocrit increase.</dc:description>
	<dc:publisher xml:lang="en">Hasanuddin University</dc:publisher>
	<dc:date>2022-02-02</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/9264</dc:identifier>
	<dc:identifier>10.20956/ejsa.v1i2.9264</dc:identifier>
	<dc:source xml:lang="en">ESTIMASI: Journal of Statistics and Its Application; Vol. 1, No. 2, Juli, 2020 : Estimasi; 58-64</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/9264/6795</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2020 ESTIMASI: Journal of Statistics and Its Application</dc:rights>
</oai_dc:dc>