ANALISIS SPASIAL KEMISKINAN DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED REGRESSION: STUDI KASUS KABUPATEN PANDEGLANG DAN LEBAK

S Sukanto; Bambang Juanda; Akhmad Fauzi; Sri Mulatsih

doi:10.14710/tataloka.21.4.669-677

DOI: https://doi.org/10.14710/tataloka.21.4.669-677

ANALISIS SPASIAL KEMISKINAN DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED REGRESSION: STUDI KASUS KABUPATEN PANDEGLANG DAN LEBAK

*S Sukanto

- Program Studi Ekonomi Pembangunan Fakultas Ekonomi, Universitas Sriwijaya, Indonesia

Bambang Juanda - Program Studi Ilmu Perencanaan Pembangunan Wilayah dan Perdesaan, Institut Pertanian Bogor, Indonesia

Akhmad Fauzi - Program Studi Ilmu Perencanaan Pembangunan Wilayah dan Perdesaan, Institut Pertanian Bogor, Indonesia

Sri Mulatsih - Program Studi Ilmu Perencanaan Pembangunan Wilayah dan Perdesaan, Institut Pertanian Bogor, Indonesia

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Abstract

Poverty is the main problem both at the national and regional development. Existing poverty alleviation programs have not paid attention to the spatial aspect. Thus the policies are often poorly targeted. This study aims to find spatial patterns of poverty in Pandeglang and Lebak districts. Geographically weighted regression (GWR) is used to analyze the poverty data in 2016. Based on the analysis, positive spatial autocorrelation is found and clustered in 25 sub-districts. Net enrollment rates tend to reduce poverty in all sub-districts. Meanwhile, village funds, electricity, and roads tend to reduce poverty rates in more than 80% of sub-districts. Independent variables have a different response in each sub-district. Therefore, the poverty alleviation program of each sub-district is adjusting to its influencing factor.

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Keywords: autocorrelation spatial; GWR; poverty; sub-district

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In Vol 21, No 4 (2019): Volume 21 No 4, November 2019

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Amara M, Ayadi M. 2013. The Local Geographies of Walfare in Tunisia: Does Neighbourhood Matter?. International Journal of Social Walfare. 22(1):90-103
Anselin L. 1988. Spatial Econometrics: Method and Models. Kluwer Academic Publisher. Dordrect Boston (US)
Bappenas. 2008. Buku Panduan Perencanaan dan Penganggaran yang Berpihak pada Masyarakat Miskin. Badan Perencanaan Pembangunan Nasional. Jakarta (ID)
Badan Pusat Statistik. 2014. Potensi Desa 2014. BPS. Jakarta (ID)
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Brundson C, Fotheringham S, Charlton M. 1998. Geographically Weighted Regression-Modeling Spatial non-Stationarity. Journal of Royal Statisticacl Society: Series D(The Statistican): 47(3):431-443
Bici R, Cela M. 2017. Education as An Important Dimension of The Poverty. European Journal of Multidisciplinary Studies.4(3):88-95
Chen KM, Wang TM. 2015. Determinants of Poverty Status in Taiwan: a Multilevel Approach. Soc Indic Res. 123(2):371-389. Tersedia pada https:// doi.org/10.1007/s11205-014-0741-4 2017 (Oct 10)
Damania R, Russ J, Wheeler, Barra AF. 2017. The Road to Growth: Measuring the Trade of between Economic Growth and Ecological Destruction. World Development. 1-27. Tersedia pada http://dx.doi.org/10.1016/j.worlddev.2017.06.001
Dreibelbis R, Green LE, Freeman MC, Saboori S, Chase RP, Rheingans R. 2013. Water, Sanitation, and Primary School Attendance: A Multi-Level Assessment Of Determinants of Household-Reported Absence in Kenya. International Journal of Educational Development. (33):457–465
Duncan DT, Kawachi I, White K, Williams DR. 2012. The Geography of Recreational Open Space: Influence of Neighborhood Racial Composition and Neighborhood Poverty. Journal of Urban Helath: Bulletin of the Newyork Academy of Medicine. 90(4):618-631
Edriss AK, Chiunda C. 2017. Interfaces Between Road and Infrastructure and Poverty in Africa: The Case of Malawi, 1994-2013. Journal of Social Economics Research. 4(1):9-21
Fotheringham A, Brunsdon C, Charlton M. 2002. Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. John Wiley&Sons (UK)
Harmes, Juanda B, Rustiadi E, Barus B. 2017. Pemetaan efek Spasial Pada Data Kemiskinan Kota Bengkulu. Journal of Regional and Rural Development Planning. 1(2):192-201
Hidalgo HM, Ormaetxe II. 2014. Long-rung effect on poverty of public expenditure in education. Working Paper. AD(2014-06):1-38
Khan FC. 2013. Heterogenety as Heterodoxy in Development Policy: Tribal Communities in Bangladesh and Kerala. International Journal of Development Issues. 12(1):4-21
Mai T, Mahadevan R. 2015. A Research Note on The Poverty Dynamics and Cost of Poverty Inequality: Case Study of Indonesia. Economic Analysis and Policy, (49):100-107
Nashwari IP, Rustiadi E, Siregar H, Juanda B. 2017. Geographicallly Weighted Regression Model for poverty Analysis in Jambi Province. Indonesian Journal of Ggeography. 49(1):42-50
Pongoh F, Sumartajaya IM, Aidi MN. 2015. Geographical Weighted Regression and Mix Geographical Weighted Regression. International Journal of Statistics and Application.5(1):1-4
Ranis G, Stewart F. 1994. Decentralisation in Indonesia. Bulletin of Indonesian Economic Studies. 30(3):41-72
Rodriquez, Pose A. 1998. The Dynamics of Regional Growth in Europe: Social and Political Factors. Oxford Clarendon, New York (US)
Rofiq A. 2014. Pertumbuhan Ekonomi dan Kemiskinan Kebijakan dan Tantangan Masa Depan. Republika. Jakarta (ID)
Rustiadi E, Saefulhakim, S, Panuju DR. 2011. Perencanaan dan Pengembangan Wilayah. Crestpent Press dan Yayasan Pustaka Obor Jakarta, Jakarta (ID)
Sasmal R., Joydeb S. 2016. Public Expenditure, Economic Growth and Poverty Alleviation. International Journal of Social Economics. 43(6):604 - 618
Saefudin A, Setiabudi NA, Achsani NA. 2011. On comparisson Between Ordinary Linear Regression and Geographically Weighted Regression: with Application to Indonesian Poverty Data. European Journal of Scientific Research. 57(2):275-285
Saefudin A, Setiabudi NA, Fitrianto A. 2012. On comparisson Between Ordinary Linear Regression and Geographically Weighted Regression: with Application to Indonesian Poverty Data. World Applied Sciences Journal. 19(2):205-210
Sinaga KP. 2013. Poverty Data Modeling in North Sumatera Province Using Geographically Weighted. International Journal of Science and Research (IJSR). 4(2):1738-1742
Vasan S, Alcantara A. 2016. GIS-Based Methods for Estimating Mising Poverty Rates & Projecting Future Rates in Census Tracts. Review of Economics & Finance. 6:1-13
Wahyuni RNT, Damayanti A. 2014. Faktor-faktor yang Menyebabkan Kemiskinan di Provinsi Papua: Analisis Spatial Heterogeneity. Jurnal Ekonomi dan Pembangunan Indonesia. 14(2):128-144
Yu Y, Zhang L, Li F, Zheng X. 2011. In the Diterminants of Public Infrastructure Spending in Chines Cities: A Spatial Econometric Perpective. The Social Science Journal. 48:458-467
Yudha EP. 2017. Implementasi Pengelolaan Keuangan Desa dan Pengaruhnya terhadap Kinerja Pembangunan Perdesaan: Studi Kasus Kabupaten Pandeglang-Banten, Sekolah Pascasarjana IPB. Bogor (ID)
Yusuf AA, Sumner A. 2014. Growth, Poverty and Inequality Under Jokowi. Bulletin of Indonesian Economic Studies. 51(3):323-348
Zhang H. 2014. The Poverty Trap of Education: Education–Poverty Connections in Western China. International Journal of Educational Development. 38(2014):47-58

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