Evaluation of the categorization of a slum environmental condition using geospatial and statistical analysis: Case study of Pipa Reja Village in Palembang City

Informal settlements or slums have become an integral condition in an urban area. Economic growth in the city attracted rural people to migrate to the city. There are more than 50% of the world population living in the urban area since 2007. Indonesia experienced the same trend, with 21.8% of the po...

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Main Authors: Hamim S.A., Usman F., Shalihat A.K.
Other Authors: 57207666760
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Published: Alpha Publishers 2023
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spelling my.uniten.dspace-252542023-05-29T16:07:36Z Evaluation of the categorization of a slum environmental condition using geospatial and statistical analysis: Case study of Pipa Reja Village in Palembang City Hamim S.A. Usman F. Shalihat A.K. 57207666760 55812540000 57211609533 Informal settlements or slums have become an integral condition in an urban area. Economic growth in the city attracted rural people to migrate to the city. There are more than 50% of the world population living in the urban area since 2007. Indonesia experienced the same trend, with 21.8% of the population are still living in the slum area. Actions have been made by the government to identify area, which is indicated as a slum area for further rejuvenating and improvements. This paper presents the spatial analysis on the infrastructure parameters and indicators which defined the slum category of Pipa Reja Village. The indicators and parameters which defined the slum category are set in the Minister of PUPR Regulation No. 2 of 2016. This study used secondary data from KOTAKU programme on baseline data of the slum parameters. The statistical analysis and geospatial analysis were conducted to evaluate the contribution of each indicator to the local slum value. The result was compared with the score value used in the Minister of PUPR Regulation No. 14 of 2018. It is found that condition of the building, condition of drainage system, waste management system, and fire protection conditions were driven the severity condition of the slum in Pipa Reja Village. There was a slightly different category of slum determined by using the percentage value approach and the scoring value approaches. Furthermore, the geospatial analysis using geographical information system can give better insight into distinguishing the critical indicators for further targeting action. � 2020 Alpha Publishers. All rights reserved. Final 2023-05-29T08:07:36Z 2023-05-29T08:07:36Z 2020 Article 2-s2.0-85094138098 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85094138098&partnerID=40&md5=b52f8b0bfc0451658f1be72bb8da04c0 https://irepository.uniten.edu.my/handle/123456789/25254 10 9 5696 5711 Alpha Publishers Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Informal settlements or slums have become an integral condition in an urban area. Economic growth in the city attracted rural people to migrate to the city. There are more than 50% of the world population living in the urban area since 2007. Indonesia experienced the same trend, with 21.8% of the population are still living in the slum area. Actions have been made by the government to identify area, which is indicated as a slum area for further rejuvenating and improvements. This paper presents the spatial analysis on the infrastructure parameters and indicators which defined the slum category of Pipa Reja Village. The indicators and parameters which defined the slum category are set in the Minister of PUPR Regulation No. 2 of 2016. This study used secondary data from KOTAKU programme on baseline data of the slum parameters. The statistical analysis and geospatial analysis were conducted to evaluate the contribution of each indicator to the local slum value. The result was compared with the score value used in the Minister of PUPR Regulation No. 14 of 2018. It is found that condition of the building, condition of drainage system, waste management system, and fire protection conditions were driven the severity condition of the slum in Pipa Reja Village. There was a slightly different category of slum determined by using the percentage value approach and the scoring value approaches. Furthermore, the geospatial analysis using geographical information system can give better insight into distinguishing the critical indicators for further targeting action. � 2020 Alpha Publishers. All rights reserved.
author2 57207666760
author_facet 57207666760
Hamim S.A.
Usman F.
Shalihat A.K.
format Article
author Hamim S.A.
Usman F.
Shalihat A.K.
spellingShingle Hamim S.A.
Usman F.
Shalihat A.K.
Evaluation of the categorization of a slum environmental condition using geospatial and statistical analysis: Case study of Pipa Reja Village in Palembang City
author_sort Hamim S.A.
title Evaluation of the categorization of a slum environmental condition using geospatial and statistical analysis: Case study of Pipa Reja Village in Palembang City
title_short Evaluation of the categorization of a slum environmental condition using geospatial and statistical analysis: Case study of Pipa Reja Village in Palembang City
title_full Evaluation of the categorization of a slum environmental condition using geospatial and statistical analysis: Case study of Pipa Reja Village in Palembang City
title_fullStr Evaluation of the categorization of a slum environmental condition using geospatial and statistical analysis: Case study of Pipa Reja Village in Palembang City
title_full_unstemmed Evaluation of the categorization of a slum environmental condition using geospatial and statistical analysis: Case study of Pipa Reja Village in Palembang City
title_sort evaluation of the categorization of a slum environmental condition using geospatial and statistical analysis: case study of pipa reja village in palembang city
publisher Alpha Publishers
publishDate 2023
_version_ 1806424523276288000
score 13.188404