PENERAPAN METODE GEOGRAPHICALLY WEIGHTED PANEL REGRESSION (GWPR) PADA KASUS KEMISKINAN DI INDONESIA

BAREKENG: JURNAL ILMU MATEMATIKA DAN TERAPAN

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Title PENERAPAN METODE GEOGRAPHICALLY WEIGHTED PANEL REGRESSION (GWPR) PADA KASUS KEMISKINAN DI INDONESIA
 
Creator Martha, Shantika
Yundari, Yundari
Rizki, Setyo Wira
Tamtama, Ray
 
Description To analyze the factor affecting poverty during several periods by considering some geographical factors, we can use a geographically weighted panel regression (GWPR) method. GWPR is a combination of the geographically weighted regression (GWR) model and the panel regression model. The research conducts to identify the factors affecting the percentage of poor people in 34 provinces in Indonesia during 2015-2019. The results show that a suitable GWPR model is a fixed-effect model (FEM) with an exponential adaptive kernel function. Referring to the model, the province is divided into four groups based on variables having a significant effect on the percentage of poor people. That factors causing the poor people percentage in Indonesia are the poor people percentage aged above 15 years old and unemployment, the people percentage aged above 15 years old and employed in the agricultural sector, the literacy rate of the poor aged between 15 to 55 years old, and the life expectancy rate.
Keywords: fixed effect model, exponential adaptive kernel.
 
Publisher MATHEMATIC DEPARTMENT, FACULTY OF MATHEMATICS AND NATURAL SCIENCES, UNIVERSITY OF PATTIMURA
 
Date 2021-06-01
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
 
Format application/pdf
 
Identifier https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/2750
10.30598/barekengvol15iss2pp241-248
 
Source BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 15 No 2 (2021): BAREKENG: Jurnal Ilmu Matematika dan Terapan; 241-248
2615-3017
1978-7227
10.30598/barekengvol15iss2year2021
 
Language eng
 
Relation https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/2750/3151
 
Rights Copyright (c) 2021 Shantika Martha, Yundari Yundari, Setyo Wira Rizki, Ray Tamtama
http://creativecommons.org/licenses/by-sa/4.0
 

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