ANALISIS SPASIAL KEMISKINAN DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED REGRESSION: STUDI KASUS KABUPATEN PANDEGLANG DAN LEBAK
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. Geograp...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Diponegoro University
2019-11-01
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| Series: | Tataloka |
| Subjects: | |
| Online Access: | https://ejournal2.undip.ac.id/index.php/tataloka/article/view/2322 |
| _version_ | 1828379087295479808 |
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| author | S Sukanto Bambang Juanda Akhmad Fauzi Sri Mulatsih |
| author_facet | S Sukanto Bambang Juanda Akhmad Fauzi Sri Mulatsih |
| author_sort | S Sukanto |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-10T03:33:05Z |
| format | Article |
| id | doaj.art-d636140e521e46278ba49e7aa9081780 |
| institution | Directory Open Access Journal |
| issn | 0852-7458 2356-0266 |
| language | English |
| last_indexed | 2024-12-10T03:33:05Z |
| publishDate | 2019-11-01 |
| publisher | Diponegoro University |
| record_format | Article |
| series | Tataloka |
| spelling | doaj.art-d636140e521e46278ba49e7aa90817802022-12-22T02:03:46ZengDiponegoro UniversityTataloka0852-74582356-02662019-11-0121466967710.14710/tataloka.21.4.669-6771700ANALISIS SPASIAL KEMISKINAN DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED REGRESSION: STUDI KASUS KABUPATEN PANDEGLANG DAN LEBAKS Sukanto0Bambang Juanda1Akhmad Fauzi2Sri Mulatsih3Program Studi Ekonomi Pembangunan Fakultas Ekonomi, Universitas SriwijayaProgram Studi Ilmu Perencanaan Pembangunan Wilayah dan Perdesaan, Institut Pertanian BogorProgram Studi Ilmu Perencanaan Pembangunan Wilayah dan Perdesaan, Institut Pertanian BogorProgram Studi Ilmu Perencanaan Pembangunan Wilayah dan Perdesaan, Institut Pertanian BogorPoverty 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.https://ejournal2.undip.ac.id/index.php/tataloka/article/view/2322autocorrelation spatialgwrpovertysub-district |
| spellingShingle | S Sukanto Bambang Juanda Akhmad Fauzi Sri Mulatsih ANALISIS SPASIAL KEMISKINAN DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED REGRESSION: STUDI KASUS KABUPATEN PANDEGLANG DAN LEBAK Tataloka autocorrelation spatial gwr poverty sub-district |
| title | ANALISIS SPASIAL KEMISKINAN DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED REGRESSION: STUDI KASUS KABUPATEN PANDEGLANG DAN LEBAK |
| title_full | ANALISIS SPASIAL KEMISKINAN DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED REGRESSION: STUDI KASUS KABUPATEN PANDEGLANG DAN LEBAK |
| title_fullStr | ANALISIS SPASIAL KEMISKINAN DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED REGRESSION: STUDI KASUS KABUPATEN PANDEGLANG DAN LEBAK |
| title_full_unstemmed | ANALISIS SPASIAL KEMISKINAN DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED REGRESSION: STUDI KASUS KABUPATEN PANDEGLANG DAN LEBAK |
| title_short | ANALISIS SPASIAL KEMISKINAN DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED REGRESSION: STUDI KASUS KABUPATEN PANDEGLANG DAN LEBAK |
| title_sort | analisis spasial kemiskinan dengan pendekatan geographically weighted regression studi kasus kabupaten pandeglang dan lebak |
| topic | autocorrelation spatial gwr poverty sub-district |
| url | https://ejournal2.undip.ac.id/index.php/tataloka/article/view/2322 |
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