Analisis Geographically Weighted Panel Regression di bidang Infrastruktur, Sosial, Kesehatan, Kependudukan, dan Pendidikan terhadap Produk Domestik Regional Bruto di Nusa Tenggara Timur

Dia Cahya Wati, diacahyawati; Lina, Ismi Rizqa; Anggraeni, Andini Setyo

doi:10.20956/ejsa.v4i2.26718

Jurnal

Analisis Geographically Weighted Panel Regression di bidang Infrastruktur, Sosial, Kesehatan, Kependudukan, dan Pendidikan terhadap Produk Domestik Regional Bruto di Nusa Tenggara Timur

ESTIMASI: Journal of Statistics and Its Application · Vol. 4 No. 2 (2023) · pp. 230–244

DOI: 10.20956/ejsa.v4i2.26718
ISSN: 2721-379X, 2721-3803
Published: 2023-08-04
Publisher: Hasanuddin University
Language: en

Abstract

Gross Regional Domestic Product (GRDP) is an important indicator of economic growth in a region. The success of regional economic growth is said to be good if the GRDP in an area has a significant effect on that area. However, economic growth in East Nusa Tenggara (NTT) has not been optimal. This is caused by economic inequality in NTT which differs between districts/cities. Therefore, the aim of this research is to find out what factors influence GRDP in NTT using Geographically Weighted Panel Regression (GWPR). The data used is sourced from the Central Statistics Agency (BPS) website. The results of the study describe that GRDP in NTT is divided into 12 groups with the adaptive bisquare kernel function and the coefficient of determination is 83.73%. The independent factors that influence GRDP in NTT are the Construction Expensive Index (IKK) and Area Area (LW) in the construction sector, the Human Development Index (IPM) in the Social sector, the Number of Poor population in the population sector, and the Literacy Rate (AMH) in the education sector. Meanwhile, the health sector did not affect GRDP in NTT.

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Co-author	Organisation	Joint articles
Nahrul Hayati	Affiliation unknown	1
Eko Sulistyono	Affiliation unknown	1

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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">Analisis Geographically Weighted Panel Regression di bidang Infrastruktur, Sosial, Kesehatan, Kependudukan, dan Pendidikan terhadap Produk Domestik Regional Bruto di Nusa Tenggara Timur</dc:title>
	<dc:creator xml:lang="en">Dia Cahya Wati, diacahyawati</dc:creator>
	<dc:creator xml:lang="en">Lina, Ismi Rizqa</dc:creator>
	<dc:creator xml:lang="en">Anggraeni, Andini Setyo</dc:creator>
	<dc:subject xml:lang="en">PDRB</dc:subject>
	<dc:subject xml:lang="en">GWPR</dc:subject>
	<dc:subject xml:lang="en">Adaptive Bisquare</dc:subject>
	<dc:subject xml:lang="en">Coefficient of Determination </dc:subject>
	<dc:description xml:lang="en">Gross Regional Domestic Product (GRDP) is an important indicator of economic growth in a region. The success of regional economic growth is said to be good if the GRDP in an area has a significant effect on that area. However, economic growth in East Nusa Tenggara (NTT) has not been optimal. This is caused by economic inequality in NTT which differs between districts/cities. Therefore, the aim of this research is to find out what factors influence GRDP in NTT using Geographically Weighted Panel Regression (GWPR). The data used is sourced from the Central Statistics Agency (BPS) website. The results of the study describe that GRDP in NTT is divided into 12 groups with the adaptive bisquare kernel function and the coefficient of determination is 83.73%. The independent factors that influence GRDP in NTT are the Construction Expensive Index (IKK) and Area Area (LW) in the construction sector, the Human Development Index (IPM) in the Social sector, the Number of Poor population in the population sector, and the Literacy Rate (AMH) in the education sector. Meanwhile, the health sector did not affect GRDP in NTT.</dc:description>
	<dc:publisher xml:lang="en">Hasanuddin University</dc:publisher>
	<dc:date>2023-08-04</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unhas.ac.id/index.php/ESTIMASI/article/view/26718</dc:identifier>
	<dc:identifier>10.20956/ejsa.v4i2.26718</dc:identifier>
	<dc:source xml:lang="en">ESTIMASI: Journal of Statistics and Its Application; Vol. 4, No. 2, Juli, 2023 : Estimasi; 230-244</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/26718/10213</dc:relation>
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