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Penggunaan Regresi Kuantil Multivariat pada Perubahan Trombosit Pasien Demam Berdarah Dengue: The Use of Multivariate Quantile Regression on Platelet Changes in Dengue Hemorrhagic Fever Patients

ESTIMASI: Journal of Statistics and Its Application · Vol. 1 No. 1 (2022) · pp. 1–9

DOI
10.20956/ejsa.v1i1.9224
ISSN
2721-379X, 2721-3803
Published
2022-02-02
Publisher
Hasanuddin University
Language
en

Abstract

Quantile regression is an extension of the regression model of conditional quantile where the distribution is derived from the response variable expressed as a co-variate function. Quantile regression can model data that contain outliers. Patterns of platelet change in DHF patients based on body temperature and white blood cells were analyzed by quantile regression using θ = 0,25; 0,50, and 0,75. Based on the parameter estimation results, the quantile θ = 0,25 and 0,75 obtained variables that affect the platelets of DHF patients are white blood cells. Significant differences from the variables in each quantile occur because of the possibility of other factors that influence the platelets of DHF patients that are not contained in the model. The difference in the influence of factors on each quantile requires an appropriate adjustment of medical measures so that efficiency can be obtained in handling DHF patients.

Keywords

Collaboration network of the authors

40 authors · 110 co-authorship links · 5 across different organisations

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 unknown3
Sri Astuti ThamrinAffiliation unknown2
Anisa KalondengAffiliation unknown2
Bunga ApriliaAffiliation unknown2
Nirwan IlyasAffiliation unknown2
Andi Kresna JayaAffiliation 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
Dewi Rahma EnteAffiliation unknown1
Azman AzmanAffiliation unknown1
Muhammad Jayzul UsrahAffiliation unknown1
AnisaAffiliation unknown1
Nurtiti SunusiAffiliation unknown1
Novilia JaoAffiliation unknown1
Najiha AlimatunAffiliation unknown1
Ainun Utari BudistiharahAffiliation unknown1
Mamik UtamiAffiliation unknown1
Fitri FitriAffiliation unknown1
Siswanto SiswantoAffiliation unknown1
Hajratul Ashwad KAffiliation unknown1
Andi Ummi Melin Aicha AichaAffiliation unknown1
Georgina Maria TinungkiAffiliation unknown1
Victor LimanAffiliation unknown1
Muhammad FadilAffiliation unknown1
Andi M Alfin BasoAffiliation unknown1
A. Elisha WulandariAffiliation unknown1
Belia Nurul FajriAffiliation unknown1
Abdullah PannuAffiliation unknown1
Alfian Akbar VallarinoAffiliation unknown1
Anugrah Nur Isnaeni RahmanAffiliation 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">Penggunaan Regresi Kuantil Multivariat pada Perubahan Trombosit Pasien Demam Berdarah Dengue: The Use of Multivariate Quantile Regression on Platelet Changes in Dengue Hemorrhagic Fever Patients</dc:title>
	<dc:creator xml:lang="en">Puteri, Widya Nauli Amalia</dc:creator>
	<dc:creator xml:lang="en">Islamiyati, Anna</dc:creator>
	<dc:creator xml:lang="en">Anisa, Anisa</dc:creator>
	<dc:subject xml:lang="en">DHF</dc:subject>
	<dc:subject xml:lang="en">Quantile</dc:subject>
	<dc:subject xml:lang="en">Multivariate</dc:subject>
	<dc:subject xml:lang="en">Regression</dc:subject>
	<dc:subject xml:lang="en">Platelet.</dc:subject>
	<dc:description xml:lang="en">Quantile regression is an extension of the regression model of conditional quantile where the distribution is derived from the response variable expressed as a co-variate function. Quantile regression can model data that contain outliers. Patterns of platelet change in DHF patients based on body temperature and white blood cells were analyzed by quantile regression using θ = 0,25; 0,50, and 0,75. Based on the parameter estimation results, the quantile θ = 0,25 and 0,75 obtained variables that affect the platelets of DHF patients are white blood cells. Significant differences from the variables in each quantile occur because of the possibility of other factors that influence the platelets of DHF patients that are not contained in the model. The difference in the influence of factors on each quantile requires an appropriate adjustment of medical measures so that efficiency can be obtained in handling DHF patients.</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/9224</dc:identifier>
	<dc:identifier>10.20956/ejsa.v1i1.9224</dc:identifier>
	<dc:source xml:lang="en">ESTIMASI: Journal of Statistics and Its Application; Vol. 1, No. 1, Januari, 2020 : Estimasi; 1-9</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/9224/6357</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2020 ESTIMASI: Journal of Statistics and Its Application</dc:rights>
</oai_dc:dc>