MARC details
| 000 -LEADER |
| fixed length control field |
02507ntm a2200373 i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
| control field |
MY-KuUP |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
| control field |
20251125105553.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS |
| fixed length control field |
t||||fr|||| 000 0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
| fixed length control field |
ta |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
| fixed length control field |
200710t20192019my a|||fram|| 000 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
| International Standard Book Number |
THE0008729(Local) |
| Qualifying information |
hardback |
| 040 ## - CATALOGING SOURCE |
| Original cataloging agency |
UMP |
| Language of cataloging |
eng |
| Transcribing agency |
UMP |
| Description conventions |
rda |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
FKASA .F395 2019 r Bc. |
| 100 0# - MAIN ENTRY--PERSONAL NAME |
| Personal name |
Siti Fazlina Mohd Suhaimi, |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
| Title |
Prediction of grey water footprint of Sungai Lembing, Bukit Sagu and Bukit Ubi water treatment plants / |
| Statement of responsibility, etc. |
Siti Fazlina Mohd Suhaimi |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
| Place of production, publication, distribution, manufacture |
Kuantan, Pahang : |
| Name of producer, publisher, distributor, manufacturer |
UMP, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2019 |
| 264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
| Date of production, publication, distribution, manufacture, or copyright notice |
© 2019 |
| 300 ## - PHYSICAL DESCRIPTION |
| Extent |
xii, 80 pages : |
| Other physical details |
illustrations (some color) ; |
| Dimensions |
30 cm. + |
| Accompanying material |
1 CD-ROM |
| 336 ## - CONTENT TYPE |
| Content type term |
text |
| Source |
rdacontent |
| 336 ## - CONTENT TYPE |
| Content type term |
text |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
| Media type term |
unmediated |
| Source |
rdamedia |
| 337 ## - MEDIA TYPE |
| Media type term |
computer |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
| Carrier type term |
volume |
| Source |
rdacarrier |
| 338 ## - CARRIER TYPE |
| Carrier type term |
computer disc |
| Source |
rdacarrier |
| 347 ## - DIGITAL FILE CHARACTERISTICS |
| File type |
text file |
| Encoding format |
PDF |
| Source |
rda |
| 500 ## - GENERAL NOTE |
| General note |
Faculty of Civil Engineering and Earth Resources |
| 502 ## - DISSERTATION NOTE |
| Dissertation note |
Project Paper (Bachelors of Civil Engineering) -- Universiti Malaysia Pahang – 2019 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
| Bibliography, etc. note |
Includes bibliographical references |
| 520 3# - SUMMARY, ETC. |
| Summary, etc. |
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. |
| 610 20 - SUBJECT ADDED ENTRY--CORPORATE NAME |
| Corporate name or jurisdiction name as entry element |
Faculty of Civil Engineering and Earth Resources |
| General subdivision |
Disertations |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
| Topical term or geographic name entry element |
Universities and colleges |
| General subdivision |
Disertations |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
| Topical term or geographic name entry element |
Theses |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Final Year Report |