Determinants of non-revenue water / Haslinda Ab Malek … [et al.]

Ab Malek, Haslinda and Zakaria, Mohamad Hafizi and Zulkifli, Muhammad Luqman and Roslan, Nur Farahin (2021) Determinants of non-revenue water / Haslinda Ab Malek … [et al.]. Malaysian Journal of Computing (MJoC), 6 (1). pp. 642-649. ISSN 2600-8238

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Water is one of the most essential needs in human daily life. Water losses or Non-Revenue Water (NRW) refers to the treated water that has been produced from water plant which did not reach to the customer. This waste of water has caused the company to suffer losses and hence, burdens the people with increasing water tariff. Moreover, it becomes one of the challenges for commercial water system management because the water company must fulfil the demand from the society which keep increasing day by day. In addition, the demand for water is increasing, as the population is growing. Despite having the rainfall throughout the year in Malaysia, many cities are experiencing water shortage and frequent water supply disruptions. Therefore, efficient management of water distribution is required to minimise the water losses and to make sure the sustainability of water reserve for a long period. This study focuses on identifying the significant factors that influence the Non-Revenue Water and modelling the data using Multiple Linear Regression Model. The sample size used in this study were 212 observations and the variables involved were Length of Connection, Number of Connection, Production Quantity, Consumption Quantity and Non-Revenue Water. It is found that the variables of Number of Connection, Consumption Quantity and Production Quantity were significant to Non-Revenue Water whereas the variable of Length of Connection was not significant. It is hoped that the result from this study can be used by the water authority company in improving the water distribution and thus reduce water losses and cost.


Item Type: Article
Email / ID Num.
Ab Malek, Haslinda
Zakaria, Mohamad Hafizi
Zulkifli, Muhammad Luqman
Roslan, Nur Farahin
Subjects: Q Science > QA Mathematics > Mathematical statistics. Probabilities
Q Science > QA Mathematics > Multivariate analysis. Cluster analysis. Longitudinal method
Q Science > QA Mathematics > Programming languages (Electronic computers)
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Computer and Mathematical Sciences
Journal or Publication Title: Malaysian Journal of Computing (MJoC)
UiTM Journal Collections: UiTM Journal > Malaysian Journal of Computing (MJoC)
ISSN: 2600-8238
Volume: 6
Number: 1
Page Range: pp. 642-649
Keywords: Non-Revenue Water, Multiple Linear Regression, Consumption
Date: April 2021
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