MARC details
| 000 -LEADER |
| fixed length control field |
02656ntm a2200373 i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
| control field |
MY-KuUP |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
| control field |
20251125105543.0 |
| 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 |
200701t20192019my a|||fram|| 000 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
| International Standard Book Number |
THE0008679(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 .A365 2019 r Bc. |
| 100 0# - MAIN ENTRY--PERSONAL NAME |
| Personal name |
Siti Ainifatihah Noor Hazlim, |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
| Title |
Determination and prediction of blue water footprint at Sungai Lembing, Bukit Sagu and Bukit Ubi water treatment plant / |
| Statement of responsibility, etc. |
Siti Ainifatihah Noor Hazlim |
| 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 ; |
| 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 majority of the earth is covered by water, but only a small percentage of that amount is available for use as clean water. Currently, one-third of the world populations are facing the water shortages. Therefore, accounting blue water footprint (WFb) will help in assessed overall water consumption for three different water treatment plant in Kuantan river basin. This paper illustrates the prediction of blue water footprint of Sungai Lembing, Bukit Sagu and Bukit Ubi WTPs throughout year 2015 to 2017. The parameters considered in the study were water intake, rainfall intensity and evaporation. In this study, water footprint manual was used to account blue water footprint throughout all water treatment plants. In order to make a prediction, Bayesian Networks (BN) and Artificial Neural Network (ANN) were used as an algorithm to train the result. Thus, prediction trend for three different water treatments has been able to be produced by using WEKA software. As a result, total blue water footprints for Sungai Lembing WTP, Bukit Sagu WTP and Bukit Ubi WTP for 2015 to 2017 were 4,905,076 mᶾ, 5,924,203 mᶾ and 26,400,519 mᶾ respectively. Results proved that ANN is the best algorithm for all WTPs as it produced lower value of root mean square error (RMSE) compared to Bayesian Network. |
| 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 |