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Estimasi Model Perubahan Indeks Harga Saham Gabungan melalui Regresi Kuantil Spline Smoothing

ESTIMASI: Journal of Statistics and Its Application · Vol. 6 No. 1 (2025) · pp. 30–37

DOI
10.20956/ejsa.v6i1.25198
ISSN
2721-379X, 2721-3803
Published
2025-02-17
Publisher
Hasanuddin University
Language
en

Abstract

Regression of nonparametric quantile is conducted on purpose to help estimating the function of regression when the assumptions about the regression curve shape are not known involving quantile values. Spline is claimed as one of the estimators commonly applied in nonparametric regression. Patterns of platelet change in Jacarta Composite Indeks (JCI) based on Dow Jones Index (IDJ) were analyszed by quantile spline smoothing using τ 0.25, 0.50, and 0.75. The analysis results show two patterns of change in the relationship of JCI and the IDJ. It can be seen from the optimal knot point for each quantile, namely 28500, 35000 and 29600, which shows that before and after the IDJ value reaches the point from the knot point, there is a tendency to decrease and then increase in the JCI data. The optimal model with the one-knot point. According to the minimum GCV value, the optimal model with the smallest GCV vaue, which is 5243.45 on quantile 0.75.

Keywords

Collaboration network of the authors

40 authors · 108 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.

  • Padjadjaran University
  • Sultan Ageng Tirtayasa University
  • Universitas Halu Oleo
  • 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
Anisa KalondengAffiliation unknown3
Anisa AnisaSultan Ageng Tirtayasa University2
Sri Astuti ThamrinAffiliation unknown2
Nirwan IlyasAffiliation unknown2
Muhammad FadilAffiliation unknown2
Andi M Alfin BasoAffiliation unknown2
Budi AyuningsihPadjadjaran University1
Iman HernamanPadjadjaran University1
Tidi DhalikaPadjadjaran University1
Destu Putra RosmawanAffiliation unknown1
Dedi RahmatPadjadjaran University1
Ansharullah AnsharullahUniversitas Halu Oleo1
Abdu Rahman BacoAffiliation unknown1
Alfiana AntohAffiliation unknown1
Yundy HafizriandaAffiliation unknown1
Widya Nauli Amalia PuteriAffiliation unknown1
Zhazha Alifkhamulki RamdhaniAffiliation unknown1
Samsul ArifinAffiliation unknown1
Bunga ApriliaAffiliation unknown1
Dewi Rahma EnteAffiliation unknown1
Muhammad Jayzul UsrahAffiliation unknown1
AnisaAffiliation unknown1
Nurtiti SunusiAffiliation unknown1
Novilia JaoAffiliation unknown1
Ainun Utari BudistiharahAffiliation unknown1
Mamik UtamiAffiliation unknown1
Fitri FitriAffiliation unknown1
Andi Kresna JayaAffiliation unknown1
Andi Ummi Melin Aicha AichaAffiliation unknown1
Afifah Mutiah NurdinAffiliation unknown1
Muh. Indirwan ArfanAffiliation unknown1
Sitti SahrimanAffiliation unknown1
Andi Isna YunitaAffiliation unknown1
A.Muthiah Nur AngrianyAffiliation unknown1
Rini JamalAffiliation unknown1
Andi FebriyantiAffiliation 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">Estimasi Model Perubahan Indeks Harga Saham Gabungan melalui Regresi Kuantil Spline Smoothing</dc:title>
	<dc:creator xml:lang="en">Ashwad K, Hajratul</dc:creator>
	<dc:creator xml:lang="en">Islamiyati, Anna</dc:creator>
	<dc:creator xml:lang="en">Siswanto, Siswanto</dc:creator>
	<dc:subject xml:lang="en">JCI</dc:subject>
	<dc:subject xml:lang="en">IDJ</dc:subject>
	<dc:subject xml:lang="en">Quantile</dc:subject>
	<dc:subject xml:lang="en">Nonparametric</dc:subject>
	<dc:subject xml:lang="en">Spline Smoothing</dc:subject>
	<dc:description xml:lang="en">Regression of nonparametric quantile is conducted on purpose to help estimating the function of regression when the assumptions about the regression curve shape are not known involving quantile values. Spline is claimed as one of the estimators commonly applied in nonparametric regression. Patterns of platelet change in Jacarta Composite Indeks (JCI) based on Dow Jones Index (IDJ) were analyszed by quantile spline smoothing using τ 0.25, 0.50, and 0.75. The analysis results show two patterns of change in the relationship of JCI and the IDJ. It can be seen from the optimal knot point for each quantile, namely 28500, 35000 and 29600, which shows that before and after the IDJ value reaches the point from the knot point, there is a tendency to decrease and then increase in the JCI data. The optimal model with the one-knot point. According to the minimum GCV value, the optimal model with the smallest GCV vaue, which is 5243.45 on quantile 0.75.</dc:description>
	<dc:publisher xml:lang="en">Hasanuddin University</dc:publisher>
	<dc:date>2025-02-17</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/25198</dc:identifier>
	<dc:identifier>10.20956/ejsa.v6i1.25198</dc:identifier>
	<dc:source xml:lang="en">ESTIMASI: Journal of Statistics and Its Application; Vol. 6, No. 1, Januari, 2025 : Estimasi; 30-37</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/25198/12586</dc:relation>
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