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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) · hlm. 1525–1536

DOI
10.30598/barekengvol19iss3pp1525-1536
ISSN
2615-3017, 1978-7227
Terbit
2025-07-01
Penerbit
PATTIMURA UNIVERSITY
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

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.

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  • Universitas Halu Oleo
  • Institut Agama Islam Negeri Kendari
  • Hasanuddin University
  • State University of Makassar
  • Afiliasi tidak diketahui
  • Organisasi berbeda
  • Organisasi sama
  • Afiliasi tidak diketahui
  • Garis lebih tebal = lebih banyak artikel bersama · lingkaran lebih besar = lebih banyak artikel
Tampilkan sebagai tabel
Rekan penulisOrganisasiArtikel bersama
Irma YahyaUniversitas Halu Oleo9
Gusti Ngurah Adhi WibawaUniversitas Halu Oleo8
Agusrawati AgusrawatiUniversitas Halu Oleo8
Agusrawati AgusrawatiAfiliasi tidak diketahui7
Lilis LaomeAfiliasi tidak diketahui6
Bahriddin AbapihiAfiliasi tidak diketahui5
Sitti Wahidah MasnaniAfiliasi tidak diketahui4
Lestari DaswanInstitut Agama Islam Negeri Kendari4
Mujadilah nurAfiliasi tidak diketahui3
Sri RahayuHasanuddin University3
Fahinu FahinuAfiliasi tidak diketahui2
Kodirun KodirunUniversitas Halu Oleo2
Irma YahyaUniversitas Halu Oleo2
Edi CahyonoUniversitas Halu Oleo2
Norma MuhtarUniversitas Halu Oleo2
Amalia DzulqaidahAfiliasi tidak diketahui2
Andi AgussalimHasanuddin University2
Zuhriah ZuhriahAfiliasi tidak diketahui2
RAHAYU RAHAYUUniversitas Halu Oleo2
Yudi YudiAfiliasi tidak diketahui2
Muhammad ArsyadUniversitas Halu Oleo2
Yuni Krisyuningsih KrisnandiAfiliasi tidak diketahui2
Indri YatiAfiliasi tidak diketahui2
Baharuddin BaharuddinAfiliasi tidak diketahui2
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 WibawaAfiliasi tidak diketahui2
Andi PatombongiAfiliasi tidak diketahui1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) https://ojs3.unpatti.ac.id/index.php/barekeng/oai, pertama di-harvest 5 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (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>
</oai_dc:dc>