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MODELING GENDER DEVELOPMENT INDEX IN SOUTHEAST SULAWESI PROVINCE USING SEMIPARAMETRIC KERNEL REGRESSION

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 19 No. 3 (2025) · pp. 1525–1536

DOI
10.30598/barekengvol19iss3pp1525-1536
ISSN
2615-3017, 1978-7227
Published
2025-07-01
Publisher
PATTIMURA UNIVERSITY
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The issue of gender equality in Southeast Sulawesi still needs further attention, as indicated by the uneven value of the Gender Development Index (GDI) in each district/city in the region. Therefore, an in-depth analysis is needed to identify factors that affect the GDI. One method that can be used is semiparametric regression with the Nadaraya-Watson estimator, which allows modeling the relationship between variables with more flexibility. This study aims to build a semiparametric regression model to identify factors that contribute to HDI in Southeast Sulawesi Province. The results of the analysis showed that the optimal bandwidth values obtained were h1= 1.57, h2=0.49, h3=2.50 and h4=4.61. The resulting model has an R2 and MSE values of 99.8% and 0.14% respectively, indicating that the model has high accuracy in explaining the overall variation in GDI.

Collaboration network of the authors

40 authors · 136 co-authorship links · 33 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 Halu Oleo
  • Institut Agama Islam Negeri Kendari
  • Hasanuddin University
  • State University of Makassar
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Irma YahyaUniversitas Halu Oleo9
Gusti Ngurah Adhi WibawaUniversitas Halu Oleo8
Agusrawati AgusrawatiUniversitas Halu Oleo8
Agusrawati AgusrawatiAffiliation unknown7
Lilis LaomeAffiliation unknown6
Sitti Wahidah MasnaniAffiliation unknown4
Lestari DaswanInstitut Agama Islam Negeri Kendari4
Bahriddin AbapihiAffiliation unknown4
Mujadilah nurAffiliation unknown3
Sri RahayuHasanuddin University3
Fahinu FahinuAffiliation unknown2
Kodirun KodirunUniversitas Halu Oleo2
Irma YahyaUniversitas Halu Oleo2
Edi CahyonoUniversitas Halu Oleo2
Norma MuhtarUniversitas Halu Oleo2
Amalia DzulqaidahAffiliation unknown2
Andi AgussalimHasanuddin University2
Zuhriah ZuhriahAffiliation unknown2
RAHAYU RAHAYUUniversitas Halu Oleo2
Yudi YudiAffiliation unknown2
Muhammad ArsyadUniversitas Halu Oleo2
Baharuddin BaharuddinAffiliation unknown2
La Ode SaidiUniversitas Halu Oleo2
Amirullah AmirullahState University of Makassar2
Hartini HartiniUniversitas Halu Oleo2
M SetiawanInstitut Agama Islam Negeri Kendari2
Nina ApriyantiInstitut Agama Islam Negeri Kendari2
Idul SetiawanInstitut Agama Islam Negeri Kendari2
Busnawir BusnawirUniversitas Halu Oleo2
Andi TenriawaruUniversitas Halu Oleo2
Baharuddin SaidUniversitas Halu Oleo2
Gusti Ngurah Adhi WibawaAffiliation unknown2
Andi PatombongiAffiliation unknown1
Cici ImayantiAffiliation unknown1
Nana SumarnaAffiliation 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 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">MODELING GENDER DEVELOPMENT INDEX IN SOUTHEAST SULAWESI PROVINCE USING SEMIPARAMETRIC KERNEL REGRESSION</dc:title>
	<dc:creator>Ampa, Andi Tenri</dc:creator>
	<dc:creator>Laome, Lilis</dc:creator>
	<dc:creator>Ridwan, Muhammad</dc:creator>
	<dc:creator>Baharuddin, Baharuddin</dc:creator>
	<dc:creator>Makkulau, Makkulau</dc:creator>
	<dc:description xml:lang="en-US">The issue of gender equality in Southeast Sulawesi still needs further attention, as indicated by the uneven value of the Gender Development Index (GDI) in each district/city in the region. Therefore, an in-depth analysis is needed to identify factors that affect the GDI. One method that can be used is semiparametric regression with the Nadaraya-Watson estimator, which allows modeling the relationship between variables with more flexibility. This study aims to build a semiparametric regression model to identify factors that contribute to HDI in Southeast Sulawesi Province. The results of the analysis showed that the optimal bandwidth values obtained were h1= 1.57, h2=0.49, h3=2.50 and h4=4.61. The resulting model has an R2 and MSE values of 99.8% and 0.14% respectively, indicating that the model has high accuracy in explaining the overall variation in GDI.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2025-07-01</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/15193</dc:identifier>
	<dc:identifier>10.30598/barekengvol19iss3pp1525-1536</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application; 1525-1536</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol19iss3year2025</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/15193/10739</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2025 Andi Tenri Ampa, Lilis Laome, Muhammad Ridwan, Baharuddin Baharuddin, Makkulau Makkulau</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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