Issue |
E3S Web of Conf.
Volume 517, 2024
The 10th International Conference on Engineering, Technology, and Industrial Application (ICETIA 2023)
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Article Number | 16001 | |
Number of page(s) | 8 | |
Section | Probability and Statistics | |
DOI | https://doi.org/10.1051/e3sconf/202451716001 | |
Published online | 15 April 2024 |
Multiple Linear Regression Modeling for Analysis of Factors Affecting COD and BOD on River Water Quality in Yogyakarta, Indonesia
1 Students Study Program of Doctoral Environmental Science, School of Postgraduate Studies, Diponegoro University, Semarang 50275, Indonesia
2 Department of Electrical Engineering, Faculty of Industrial Technology, Institut Sains & Teknologi AKPRIND Yogyakarta, Indonesia
3 Department of Environmental Engineering, Faculty of Engineering, Diponegoro University, Semarang 50275, Indonesia
4 Study Program of Doctoral Environmental Science, School of Postgraduate Studies, Diponegoro University, Semarang 50275, Indonesia
5 Department of Statistics, Faculty of Science and Mathematics, Diponegoro University, Semarang 50275, Indonesia
* Corresponding author: m_andang@akprind.ac.id
Many factors can affect the quality of river water in DIY, both the activities of the population and industry. Several river water quality parameters that can be used to determine the health condition of river water are Chemical Oxygen Demand (COD) and Biological Oxygen Demand (BOD). This study tested the effect of TSS and DO on BOD and COD in 10 rivers in DIY. The method used is multiple linear regression modeling. Based on hypothesis testing in multiple linear regression with a significance level of 5%, it is found that TSS and DO significantly affect BOD and COD conditions in 2019. Furthermore, in 2020 only DO significantly affects COD. The prediction result is that if TSS is high then BOD and COD will be predicted to have high value. If DO is high then COD and BOD will be predicted to be low.
© The Authors, published by EDP Sciences, 2024
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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