Identifikasi Spasial Faktor-Faktor yang Mempengaruhi Permukiman Kumuh di Kota Bekasi

Retno Wijayanti; Atang Sutandi; Andrea Emma Pravitasari

doi:10.14710/tataloka.22.4.573-585

DOI: https://doi.org/10.14710/tataloka.22.4.573-585

Identifikasi Spasial Faktor-Faktor yang Mempengaruhi Permukiman Kumuh di Kota Bekasi

*Retno Wijayanti - Sekolah Pascasarjana Institut Pertanian Bogor, Indonesia

Atang Sutandi - Departemen Ilmu Tanah dan Sumberdaya Lahan, Institut Pertanian Bogor, Indonesia

Andrea Emma Pravitasari - Departemen Ilmu Tanah dan Sumberdaya Lahan, Institut Pertanian Bogor, Indonesia

BibTex Citation Data :

@article{tataloka5054,
    author = {Retno Wijayanti and Atang Sutandi and Andrea Pravitasari},
    title = {Identifikasi Spasial Faktor-Faktor yang Mempengaruhi Permukiman Kumuh di Kota Bekasi},
    journal = {TATALOKA},
  volume = {22},
    number = {4},
    year = {2020},
    keywords = {slum area; spatial pattern; GWR},
    abstract = {Bekasi City is buffer city for Jakarta City which have high attraction for people to urbanize. It have consequences of the emergence of many urban areas issues such as slum area. The slums handling by the government has been running intensively since 2016. Objectives of the study were 1) Analyze of spatial distribution patterns in slum area in Bekasi City 2) Analyze of key factors which affects slum area in Bekasi City. Data were analyzed using spatial analysis, i.e Moran Index analysis, spatial mean center analysis, spatial standart deviation analysis, multiple linear regression and Geographically Weighted Regression (GWR). The result of the analysis showed that the spatial pattern of slum areas in Bekasi City in 2016 and 2018 has changed. The Morans Index analysis in 2016 showed that the spatial pattern of the slum distributuon was clustered pattern, whereas in 2018 was random pattern. The spatial mean center and standart deviation ellips analysis showed that the slums moving towards southern of Bekasi City. The influenced factor of slum in 2016 was the number of low income people. Meanwhile in 2018, it were the number of of slums in each district, the percentage of poor children who does not attending school, the value of district development index, the number of low income people and the percentage of residential buildings that does not own building permit. The GWR results showed the five factors above have different effects on each location. Based on the result of the study showed that the slums is not only influenced by the physical factors but alson non physical factors caused the percentage of slum families increasing in Bekasi City.},
   issn = {2356-0266},   pages = {573--585}  doi = {10.14710/tataloka.22.4.573-585},
    url = {https://ejournal2.undip.ac.id/index.php/tataloka/article/view/5054}
}

Citation Format:

Abstract

Bekasi City is buffer city for Jakarta City which have high attraction for people to urbanize. It have consequences of the emergence of many urban areas issues such as slum area. The slums handling by the government has been running intensively since 2016. Objectives of the study were 1) Analyze of spatial distribution patterns in slum area in Bekasi City 2) Analyze of key factors which affects slum area in Bekasi City. Data were analyzed using spatial analysis, i.e Moran Index analysis, spatial mean center analysis, spatial standart deviation analysis, multiple linear regression and Geographically Weighted Regression (GWR). The result of the analysis showed that the spatial pattern of slum areas in Bekasi City in 2016 and 2018 has changed. The Morans Index analysis in 2016 showed that the spatial pattern of the slum distributuon was clustered pattern, whereas in 2018 was random pattern. The spatial mean center and standart deviation ellips analysis showed that the slums moving towards southern of Bekasi City. The influenced factor of slum in 2016 was the number of low income people. Meanwhile in 2018, it were the number of of slums in each district, the percentage of poor children who does not attending school, the value of district development index, the number of low income people and the percentage of residential buildings that does not own building permit. The GWR results showed the five factors above have different effects on each location. Based on the result of the study showed that the slums is not only influenced by the physical factors but alson non physical factors caused the percentage of slum families increasing in Bekasi City.

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Keywords: slum area; spatial pattern; GWR

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Language : ID

In Vol 22, No 4 (2020): Volume 22 No. 4, November 2020

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