Issue |
E3S Web Conf.
Volume 200, 2020
The 1st Geosciences and Environmental Sciences Symposium (ICST 2020)
|
|
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Article Number | 04005 | |
Number of page(s) | 6 | |
Section | Human and Natural Resources | |
DOI | https://doi.org/10.1051/e3sconf/202020004005 | |
Published online | 23 October 2020 |
Population characteristics and distribution patterns of slum areas in Palembang City: Getis ord gi* analysis
1
Doctoral Program in Population Study, Postgraduate School, Universitas Gadjah Mada, Indonesia
2
Population Study Program, Postgraduate School, Universitas Gadjah Mada, Indonesia
3
Center for Population and Policy Studies, Universitas Gadjah Mada, Indonesia
* Corresponding author: andri.kurniawan@ugm.ac.id
The paper aims to describe the population characteristics and the distribution patterns of slums in Palembang City. The research employs a quantitative method with 382 respondents. The data are analyzed using cross-tabulation of IBM SPSS 23 to know the population characteristics. Meanwhile, the distribution patterns of slums are analyzed by observing the sample distribution through the proportional random sampling technique. It is carried out by calculating the number of buildings of each area and noting the coordinates of each sample using GPS essentials application. The data are recorded and inserted into the sample spots on the map, which were then analyzed using the High-Low Clustering Report of Getis Ord General Gi*, to see the distribution pattern, especially the cold spot and hot spot, through ArcMap 103 program. The research found that non-migrant married Moslems dominate the population of Palembang city, with the average occupation is labor or manual worker. The slum distribution forms a low cluster pattern, meaning that it has a low value. The value is due to the government’s effort to manage the city and the development of the market sector, limiting the slum distribution. Getis Ord Gi* analysis revealed that the slum area in the city center and within a dense population is a cold spot (low cluster), while those far from the city center yet are still crowded are hot spots (high cluster).
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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