MATEC Web Conf.
Volume 192, 2018The 4th International Conference on Engineering, Applied Sciences and Technology (ICEAST 2018) “Exploring Innovative Solutions for Smart Society”
|Number of page(s)||4|
|Section||Track 2: Mechanical, Mechatronics and Civil Engineering|
|Published online||14 August 2018|
The modelling of ground water quality in urban area based on demographics factor and building coverage ratio by using geographically weighted regression approach (case study in Jakarta, Indonesia)
Civil Engineering Department, Faculty of Engineering, Universitas Indonesia, Depok, Indonesia
2 Mathematics Department, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok, Indonesia
Corresponding author: fitria65@@eng.ui.ac.id
The population density as consequences of urbanisation in certain area may cause the occurrence of land utility shifting from natural site to impervious. Thus, this imperivious cover can be used as indicator of environment quality, particularly the water quality, such being the case of Jakarta, that 80% of ground water sample in Jakarta has been contaminated by E.Coli. Due to this condition, there are indicators which might be correlated with the water quality, namely building coverage ratio (BCR) and demographic factors such as population and building density. This study argues the influence of those three factors toward the ground water quality. The aim of this study is to formulate a spatial regression-correlation model between those three factors with the main indicator of water quality, namely E.Coli. The sampling data were obtained from a densely populated areas in Duren Sawit sub-district, in Jakarta. In term of statistical process, Geographically Weighted Regression (GWR) was used to analyse the spatial data. The result suggested that the value of R2 at 68.9% and the largest influence of E.Coli value in this models was more affected by the BCR rather than by demographic factors. This outcome would be an early recommendation for Jakarta.
© The Authors, published by EDP Sciences, 2018
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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