Identifying the significant factors in treated water using binary logistic regression model : a class study in Perlis, Malaysia
Master of Science in Engineering Mathematics
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Universiti Malaysia Perlis (UniMAP)
2017
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| Online Access: | http://dspace.unimap.edu.my:80/xmlui/handle/123456789/76683 |
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my.unimap-766832022-11-02T02:11:48Z Identifying the significant factors in treated water using binary logistic regression model : a class study in Perlis, Malaysia Fatin Munawwarah, Aziz Amran, Ahmed, Prof. Dr. Water quality Water quality bioassay Disinfection and disinfectants Regression analysis Master of Science in Engineering Mathematics The production of disinfection by-product (DBP) is result of reaction between disinfection agent with the natural organic matter, bromide or iodide in the water. Trihalomethane (THM) is the main group of DBP found in many chlorinated water. THM consist of trichloromethane (TCM), dibromochloromethane (DBCM), dichlorobromomethane (DCBM) and tribromomethane (TBM). In this study, data of treated water taken from year 2015 in state of Perlis, Malaysia. For sampling point, Perlis was divided into four district (Kangar, Jejawi, Kuala Perlis and Arau) and water quality variables measured are water pH, water temperature, residual chlorine, TCM readings, the purified water and non purified water. A binary logistic regression was proposed to predict the probability of purified water in housing area using all the continuous variables measured. Correlation between TCM formation and these variables were estimated using a Spearman’s correlation test. A negative moderate correlation exist between residual chlorine and TCM in Arau (p= -0.537, p<0.05) . Besides that, there exist a strong negative correlation between water pH and residual chlorine in Jejawi (p= -0.603, p<0.01) but no correlation exist between pH and TCM. Same result obtained for district Kangar (p= -0.722, p<0.01) . Additionally, when correlation analysis did on the overall data, there exist a negative weak interaction between water temperature and TCM formation in Perlis (p= -0.222, p<0.05) . However, some variables such as pH and residual chlorine did not show any influence towards TCM formation. Results of adjusted Welch’s F test suggesting that there is significant mean different of TCM level in every district in Perlis. Significant pairwise difference obtained between Kangar (x~= -0.189, SD=0.171) with Kuala Perlis (x~= -0.0478, SD=0.0667) with mean difference of 0.14095. Besides that, Jejawi was (x~= -0.1852, SD=0.0816) significantly higher of TCM mean compared to Kuala Perlis with mean difference of 0.1374 and Arau (x~= -0.092, SD=0.063) with mean difference of 0.09335. From binary logistic regression model, residual chlorine and TCM have influence on the purified water prediction. On the overall, the average TCM concentration in Perlis is 0.13mg/L (130 ppb) which is under acceptable maximum value of TCM while other THM such as DBCM, DCBM, and TBM are non-quantifiable because of concentration below detection limit. 2017 2022-11-02T02:11:48Z 2022-11-02T02:11:48Z Dissertation http://dspace.unimap.edu.my:80/xmlui/handle/123456789/76683 en Universiti Malaysia Perlis (UniMAP) Universiti Malaysia Perlis (UniMAP) Institute of Engineering Mathematics |
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Universiti Malaysia Perlis |
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Asia |
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Malaysia |
| content_provider |
Universiti Malaysia Perlis |
| content_source |
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http://dspace.unimap.edu.my/ |
| language |
English |
| topic |
Water quality Water quality bioassay Disinfection and disinfectants Regression analysis |
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Water quality Water quality bioassay Disinfection and disinfectants Regression analysis Fatin Munawwarah, Aziz Identifying the significant factors in treated water using binary logistic regression model : a class study in Perlis, Malaysia |
| description |
Master of Science in Engineering Mathematics |
| author2 |
Amran, Ahmed, Prof. Dr. |
| author_facet |
Amran, Ahmed, Prof. Dr. Fatin Munawwarah, Aziz |
| format |
Dissertation |
| author |
Fatin Munawwarah, Aziz |
| author_sort |
Fatin Munawwarah, Aziz |
| title |
Identifying the significant factors in treated water using binary logistic regression model : a class study in Perlis, Malaysia |
| title_short |
Identifying the significant factors in treated water using binary logistic regression model : a class study in Perlis, Malaysia |
| title_full |
Identifying the significant factors in treated water using binary logistic regression model : a class study in Perlis, Malaysia |
| title_fullStr |
Identifying the significant factors in treated water using binary logistic regression model : a class study in Perlis, Malaysia |
| title_full_unstemmed |
Identifying the significant factors in treated water using binary logistic regression model : a class study in Perlis, Malaysia |
| title_sort |
identifying the significant factors in treated water using binary logistic regression model : a class study in perlis, malaysia |
| publisher |
Universiti Malaysia Perlis (UniMAP) |
| publishDate |
2017 |
| url |
http://dspace.unimap.edu.my:80/xmlui/handle/123456789/76683 |
| _version_ |
1751537957903269888 |