ANALISIS REGRESI SPASIAL DURBIN UNTUK MENGANALISIS FAKTOR-FAKTOR YANG BERHUBUNGAN DENGAN PERSENTASE PENDUDUK MISKIN

Yulita Putri Lokang; Ignatius Aris Dwiatmoko

doi:10.33557/jurnalmatrik.v21i2.565

Yulita Putri Lokang Universitas Sanata Dharma
Ignatius Aris Dwiatmoko Universitas Sanata Dharma

DOI: https://doi.org/10.33557/jurnalmatrik.v21i2.565

Keywords: percentage of poor people, spasial Durbin regression, maximum likelihood method, Moran index test

Abstract

The percentage of poor people is the percentage of the population who have a monthly per capita expenditure below the poverty line. In this study, spatial Durbin regression used to know the factors which is giving effect to the percentage of poor population with maximum likelihood method to estimate parameters. This method used because it can maximize the probability of occurrence of each parameter. From 6 independent variables that are thought to be related to the percentage of poor people, there are only 4 independent variables that can be modeled by the spatial Durbin regression model because of the presence of significant spatial autocorrelation based on the Moran Index test. That are school participation rates aged 16-18 years, inflation, life expectancy at birth, and the human development index. The measure of the goodness of the Durbin spatial regression model calculated by looking for the value of R² is 68,4%

References

[1] A. Widarjono, Ekonometrika Pengantar dan Aplikasinya. Jakarta: Ekonosia, 2013
[2] R. Kurniawan, Y. Budi, Analisis Regresi: dasar dan penerapannya dengan R. Jakarta: Kencana, 2016.
[3] Schabenberger , Gotway, “Statistical Methods for Spatial Data Analysis”. 2005. Chapman & Hall/CRC.
[4] BPS Provinsi Jawa Tengah, tersedia di https://jateng.bps.go.id/. [diakses pada tanggal 04-03-2019]
[5] M. Aldino, Analisis Kemiskinan di Jawa Tengah, 2018
[6] N. Oktaviani, Analisis regresi spasial pada data jumlah penduduk miskin provinsi lampung pada tahun 2017, 2018.
[7] L. Putu Safitri Pratiwi, I Gusti Ayu Made, M. susilawati, “Analisis Kemiskinan dengan Pendekatan Model Regresi Spasial Durbin,” E-Jurnal Matematika, vol. 2, no. 3, hal. 11-16, 2013.
[8] R. Kosfeld, “Spatial Econometrics”. 2006.
[9] L. Anselin, Spatial Econometrics: Methods and models. Netherlands: Kluwer Academic Publisher, 1988.
[10] R. Bekti., R. Anita, Sutikno, “Maximum likelihood estimation for spatial durbin model” Journal of Mathematics and Statistics, vol. 9, no. 3, hal. 169-174, 2013
[11] D. Gujarati, Basic Econometrics 4th edition. New York: Mc. Graw-Hill, 2003.