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

  • Shantika Martha Universitas Tanjungpura
  • Yundari Yundari Universitas Tanjungpura
  • Setyo Wira Rizki Universitas Tanjungpura
  • Ray Tamtama Universitas Tanjungpura
DOI: https://doi.org/10.30598/barekengvol15iss2pp241-248
Keywords: fixed effect model, exponential adaptive kernel

Abstract

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.

Downloads

Download data is not yet available.

References

A. Khomsan, A. Dharmawan, S. Saharuddin, A. Alfiasari, D. Sukandar, and H. Syarief, Indikator Kemiskinan dan Misklasifikasi Orang Miskin. Jakarta: Yayasan Pustaka Obor Indonesia, 2015.

BPS, Perhitungan dan Analisis Kemiskinan Makro Indonesia. Jakarta: Badan Pusat Statistik, 2017.

A. Qur’ani, “Pemodelan Geographically Weighted Panel (GWR-Panel) sebagi Pendekatan Model Geographically Weighted Regression(GWR) dengan Menggunakan Fixed Effect Model Time Trend,†J. Mhs. Stat., vol. 2, no. 3, 2014.

N. Rahayu, Geographically Weighted Panel Regression untuk Pemodelan Persentase Penduduk Miskin di Provinsi Jawa Tengah(Tesis). Surabaya: FMIPA Institut Teknologi Sepuluh Nopember, 2017.

A. Widarjono, Ekonometrika: Pengantar dan Aplikasinya. Yogyakarta: UPP STIM YKPN, 2016.

C. Hsiao, Analysis of Panel Data, Second Edi. New York: Cambridge University Press, 2003.

H. Greene, Econometric Analysis. New Jersey: Prentice-Hall.

A. Melliana and I. Zain, “Analisis Statistika Faktor yang Mempengaruhi Indek Pembangunan Manusia di Kabupaten/Kota Provinsi Jawa Timur dengan menggunakan Regresi Panel,†J. Sains dan Seni POMITS, vol. 2, no. 2, pp. 237–242, 2013.

S. Sutro, Y. Yundari, and S. Martha, “Pemodelan Fixed Effect Geographically Weighted Panel Regression untuk Indeks Pembangunan Manusia di Kalimantan Barat,†Bul. Ilm. Mat. , Stat. dan Ter., vol. 9, no. 3, pp. 413–422, 2020.

D. Yu, “Exploring Spatiotemporally Varying Regressed Relationship: The Geographically Weighted Panel Regression Analysis,†Int. Arch. Photogrammety, Remote Sens. Spat. Inf. Sci., vol. 38, no. 2, pp. 134–139, 2010.

R. Caraka and H. Yasin, Geographically Weighted Regression(GWR): Sebuah Pendekatan Regresi Geografis. Yogyakarta: Mobius, 2017.

F. Bruna and D. Yu, “Geographically Weighted Panel regression,†A Coruna 24-26, 2013.

R. Cai, D. Yu, and M. Oppenheimer, “Estimating the Spatially Varying Responses of Corn Yields to Weather Variation using Geographically Weighted Panel regression,†J. Agric. Resour. Econ., vol. 39, no. 2, 2014.

S. Meutuah, H. Yasin, and D. Maruddani, “Pemodelan Fixed Effect Geographically Weighted Panel Regression untuk Indeks Pembangunan Manusia di Jawa tengah,†J. Gaussian, vol. 6, no. 2, pp. 241–250, 2017.

Cities Indonesia, “Cities in Indonesia.†https://www.latlong.net/category/cities-103-15.html.

Published
2021-06-01
How to Cite
[1]
S. Martha, Y. Yundari, S. Rizki, and R. Tamtama, “PENERAPAN METODE GEOGRAPHICALLY WEIGHTED PANEL REGRESSION (GWPR) PADA KASUS KEMISKINAN DI INDONESIA”, BAREKENG: J. Math. & App., vol. 15, no. 2, pp. 241-248, Jun. 2021.
Issue
Vol 15 No 2 (2021): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Section
Articles

Authors who publish with this Journal agree to the following terms:

  1. Author retain copyright and grant the journal right of first publication with the work simultaneously licensed under a creative commons attribution license that allow others to share the work within an acknowledgement of the work’s authorship and initial publication of this journal.
  2. Authors are able to enter into separate, additional contractual arrangement for the non-exclusive distribution of the journal’s published version of the work (e.g. acknowledgement of its initial publication in this journal).
  3. Authors are permitted and encouraged to post their work online (e.g. in institutional repositories or on their websites) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published works.