MODELLING DOMESTIC WATER DEMAND IN MALAYSIA TO IDENTIFY INFLUENCING FACTORS: A COMPARATIVE ANALYSIS

Water crises are often experienced by many developing countries worldwide. Predicting future domestic water demand and identifying the influential factors are vital to managing water supply effectively. This study aims to determine the best predictive models among Multiple Linear Regression (MLR), M...

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Published in:Journal of Sustainability Science and Management
Main Author: JEFRI N.; SHAADAN N.
Format: Article
Language:English
Published: Universiti Malaysia Terengganu 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199333196&doi=10.46754%2fjssm.2024.06.004&partnerID=40&md5=0757d0edd7e086863aa21807e7f788a1
id 2-s2.0-85199333196
spelling 2-s2.0-85199333196
JEFRI N.; SHAADAN N.
MODELLING DOMESTIC WATER DEMAND IN MALAYSIA TO IDENTIFY INFLUENCING FACTORS: A COMPARATIVE ANALYSIS
2024
Journal of Sustainability Science and Management
19
6
10.46754/jssm.2024.06.004
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199333196&doi=10.46754%2fjssm.2024.06.004&partnerID=40&md5=0757d0edd7e086863aa21807e7f788a1
Water crises are often experienced by many developing countries worldwide. Predicting future domestic water demand and identifying the influential factors are vital to managing water supply effectively. This study aims to determine the best predictive models among Multiple Linear Regression (MLR), Multi-layer Perceptron (MLP), and Radial Basis Function (RBF) Neural Networks as well as to identify the significant influential factors towards domestic water demand. Based on the yearly records from 2000 to 2018 obtained from the Malaysian Water Association, the Department of Environment, and the Department of Statistics Malaysia the analysis results indicate an increasing pattern of domestic water in Malaysia with the demand for non-domestic water twice lower than domestic water. Based on RMSE and R-squared, Multi-layer Perceptron is the best model for predicting domestic water demand. The MLR model shows that the two most significant influential factors towards domestic water demand are price and design capacity, with negative and positive relationships. The results describe that an increase in price affects a decrease in water demand, while an increase in design capacity will reduce the water demand. The findings suggest that the water utilities in Malaysia should focus more on these identified factors. © (2024) UMT Press
Universiti Malaysia Terengganu
18238556
English
Article

author JEFRI N.; SHAADAN N.
spellingShingle JEFRI N.; SHAADAN N.
MODELLING DOMESTIC WATER DEMAND IN MALAYSIA TO IDENTIFY INFLUENCING FACTORS: A COMPARATIVE ANALYSIS
author_facet JEFRI N.; SHAADAN N.
author_sort JEFRI N.; SHAADAN N.
title MODELLING DOMESTIC WATER DEMAND IN MALAYSIA TO IDENTIFY INFLUENCING FACTORS: A COMPARATIVE ANALYSIS
title_short MODELLING DOMESTIC WATER DEMAND IN MALAYSIA TO IDENTIFY INFLUENCING FACTORS: A COMPARATIVE ANALYSIS
title_full MODELLING DOMESTIC WATER DEMAND IN MALAYSIA TO IDENTIFY INFLUENCING FACTORS: A COMPARATIVE ANALYSIS
title_fullStr MODELLING DOMESTIC WATER DEMAND IN MALAYSIA TO IDENTIFY INFLUENCING FACTORS: A COMPARATIVE ANALYSIS
title_full_unstemmed MODELLING DOMESTIC WATER DEMAND IN MALAYSIA TO IDENTIFY INFLUENCING FACTORS: A COMPARATIVE ANALYSIS
title_sort MODELLING DOMESTIC WATER DEMAND IN MALAYSIA TO IDENTIFY INFLUENCING FACTORS: A COMPARATIVE ANALYSIS
publishDate 2024
container_title Journal of Sustainability Science and Management
container_volume 19
container_issue 6
doi_str_mv 10.46754/jssm.2024.06.004
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199333196&doi=10.46754%2fjssm.2024.06.004&partnerID=40&md5=0757d0edd7e086863aa21807e7f788a1
description Water crises are often experienced by many developing countries worldwide. Predicting future domestic water demand and identifying the influential factors are vital to managing water supply effectively. This study aims to determine the best predictive models among Multiple Linear Regression (MLR), Multi-layer Perceptron (MLP), and Radial Basis Function (RBF) Neural Networks as well as to identify the significant influential factors towards domestic water demand. Based on the yearly records from 2000 to 2018 obtained from the Malaysian Water Association, the Department of Environment, and the Department of Statistics Malaysia the analysis results indicate an increasing pattern of domestic water in Malaysia with the demand for non-domestic water twice lower than domestic water. Based on RMSE and R-squared, Multi-layer Perceptron is the best model for predicting domestic water demand. The MLR model shows that the two most significant influential factors towards domestic water demand are price and design capacity, with negative and positive relationships. The results describe that an increase in price affects a decrease in water demand, while an increase in design capacity will reduce the water demand. The findings suggest that the water utilities in Malaysia should focus more on these identified factors. © (2024) UMT Press
publisher Universiti Malaysia Terengganu
issn 18238556
language English
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