PEMODELAN ANALISIS REGRESI SPASIAL PADA KASUS KEMISKINAN KABUPATEN/KOTA DI JAWA TIMUR  TAHUN 2020

Kiki Laila Nirmala; Wara Pramesti

doi:10.35580/variansiunm24477

PEMODELAN ANALISIS REGRESI SPASIAL PADA KASUS KEMISKINAN KABUPATEN/KOTA DI JAWA TIMUR TAHUN 2020

Kiki Laila Nirmala⁽¹⁾, Wara Pramesti^(2*),

(1) Program Sudi Statistika, UNIPA Surabaya, 60234 , Surabaya, Indonesia
(2) Program Sudi Statistika, UNIPA Surabaya, 60234 , Surabaya, Indonesia
(*) Corresponding Author

DOI: https://doi.org/10.35580/variansiunm24477

Abstract

The percentage of poor people is still a problem in Indonesia, and one of them is in East Java Province, where based on the results of the SUSENAS, in the March 2020 period, the country's poverty line increased by 2.93% or increased by Rp. 11,829,- per capita per month, ie from Rp. 404,172,- per capita per month in September 2019 to Rp. 416,001,- per capita per month in March 2020. Although the increase is not high, it is still a concern. The increase and decrease in the percentage of poverty of course some factors influence, and to determine the influencing factors can be used but presents the possibility of regression analysis is also influenced by the surrounding conditions so that the assumption of independent possibility is not met. To overcome this problem, a Spatial Regression approach can be used, which in the analysis has taken into account the surrounding area. The results show that the percentage is influenced by factors that have a significant effect, also influenced by neighbors, and the appropriate spatial regression analysis modeling is the Spatial Autoregressive Model (SAR).

Keywords: Poverty, Spatial Regression, SAR

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