Siti Fazlina Mohd Suhaimi creator author. text abstract or summary my 2019 2019 monographic eng xii, 80 pages : illustrations (some color) ; 30 cm. + 1 CD-ROM The most important factors affecting water scarcity in local and global and the availability of fresh water resources are not only a growing world population but also an increasing water demand. From this study, the level pollution of water in Kuantan river basin is recorded according to each water treatment plant (WTP) and grey water footprint assessment was used as an approach to account the total amount of freshwater used to assimilate the pollutant‟s concentration. Hence, this study is aimed to calculate the total grey water footprint, to predict the trend of total grey water footprint and to compare the best algorithm between Artificial Neural Network (ANN) and Bayesian Networks (BN) in grey water footprint prediction at Sungai Lembing WTP, Bukit Sagu WTP and Bukit Ubi WTP in 2015 until 2017. As the end result of this study, the total grey water footprint in Sungai Lembing, Bukit Sagu and Bukit Ubi water treatment plant in Kuantan river basin is calculated. Prediction trend of total grey water footprint in three water treatment plants has able to be produced. Artificial Neural Network (ANN) algorithm is also be chosen as the best algorithm. specialized Siti Fazlina Mohd Suhaimi Faculty of Civil Engineering and Earth Resources Project Paper (Bachelors of Civil Engineering) -- Universiti Malaysia Pahang – 2019 Includes bibliographical references Faculty of Civil Engineering and Earth Resources Disertations Universities and colleges Disertations Theses THE0008729(Local) UMP 200710 20251125105553.0 eng