Correlation analysis and multilinear regression model for prediction on solid waste generation in Malaysia

Faridah Zulkipli, and Zulkifli Mohd Nopiah, and Noor Ezlin Ahmad Basri, and Cheng, Jack Kie (2021) Correlation analysis and multilinear regression model for prediction on solid waste generation in Malaysia. Jurnal Kejuruteraan, 33 (3). pp. 439-445. ISSN 0128-0198

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Official URL: https://www.ukm.my/jkukm/volume-333-2021/

Abstract

Increased volumes of solid waste generation continue unabated due mainly to rapid population increase, urban migration, economic enhancements, and modern lifestyles. Two significant factors contributing directly to the higher volumes of solid waste generation are population and gross domestic product (GDP). In Phase 1 of this study, a correlation analysis with a Pearson coefficient of more than 93% (r > 0.93) shows a strong positive linear relationship between the amount of solid waste generation and population and GDP. Phase 2 provides a multilinear regression analysis and the development of a regression model. They indicate that a 1-unit increment in the amount of solid waste generation is caused by 0.06 of the population and 0.119 of GDP while ßo remains constant at 124.449. Therefore, the multilinear regression model in this study can be applied by solid waste management authorities in Malaysia to accurately forecast future solid waste generation volumes. However, further investigation on other significance factors are suggested for future work in order to develop a holistic model for solid waste management in Malaysia.

Item Type:Article
Keywords:Solid waste generation; Correlation analysis; Multilinear regression model; Population; Gross domestic product
Journal:Jurnal Kejuruteraan
ID Code:18753
Deposited By: ms aida -
Deposited On:07 Jun 2022 04:16
Last Modified:10 Jun 2022 00:46

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