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Octafinnanda Ummu Fairuzdhiya
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ANALISIS SPASIAL PENGARUH TINGKAT PENGANGGURAN TERHADAP KEMISKINAN DI INDONESIA (Studi Kasus Provinsi Jawa Tengah) Rahmawati, Rita; Safitri, Diah; Fairuzdhiya, Octafinnanda Ummu
MEDIA STATISTIKA Vol 8, No 1 (2015): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (507.192 KB) | DOI: 10.14710/medstat.8.1.23-30

Abstract

Poverty is still being one of big problems in Indonesia. Any efforts are done to find a solution for this problem. Poverty itself can be caused of the high unemployment that occurs. With a number of unemployment, it will be lower income thus reducing also purchasing power and the ability to meet the needs of life thus causing poverty. This study analyzed the impact of unemployment to the poverty as involving spatial factors, using spatial regression analysis. Used data on poverty and unemployment in each regency in the central java, the analysis shows that based on likelihood ratio test, obtained LR test value 6,038 or p-value 0,014001 which means there is a spatial correlation. By testing model simultaneously nor individually using Breusch-Pagan test and Wald test, it show that both are significant, with BP = 6,7094; df = 1; p-value = 0,009591 and Wald statistic = 7,0238; p-value = 0,0080434. The results means there are spatial element in the relations between unemployment and poverty in central java so that SEM is more proper used than ordinary linear regression. Keywords: Spatial Error Model (SEM), Spatial Autocorrelation, Spatial Heterogeneity
ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI KEMISKINAN DI JAWA TENGAH MENGGUNAKAN MODEL GALAT SPASIAL Octafinnanda Ummu Fairuzdhiya; Rita Rahmawati; Agus Rusgiyono
Jurnal Gaussian Vol 3, No 4 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (652.239 KB) | DOI: 10.14710/j.gauss.v3i4.8089

Abstract

Poverty is one of problems in developing country like Indonesia. From year to year, poverty in Central Java has decreased. This study is aimed to know the poverty model in Central Java by using Spatial Error Model. This research uses data from the number of poor people in Central Java in 2012. Spatial Error Model is a spatial method that showed spatial autocorrelation in the error. In Spatial Error Model, there are spatial dependency effect and spatial heterogenity. The variables that significantly affect the number of poor people in Central Java through Spatial Error Model are the percentage of 10 years old–over population with the highest education is primary school ( X2) and the number of households that have access to reliable drinking water (X3). This Spatial Error Model results R2 are 75,39% with the AIC are 63,36. It is better than regression model of Ordinary Least Square (OLS) which produces 66,3% of R2 with AIC are 69,286. It showed the poverty model in Central Java by using Spatial Error Model is better than regression model of Ordinary Least Square (OLS) and in OLS assumption of homoskedasticity not significant. Keywords: Poverty, Regression, Ordinary Least Square, Spastial Error Model
Co-Authors Agus Rusgiyono Diah Safitri Rita Rahmawati