Sains Malaysiana 35(2):1-7 (2006)

 

Equation Modeling of Sembulan River, Sabah, as a Case Study

using Backward Stepwise Multiple Linear Regression

(Permodelan Persamaan bagi Sungai Sembulan Sebagai Kajian Kes Menggunakan

Regresi Linear Berganda Langkah Demi Langkah Ke belakang)

 

 

Rita Sundari, Musa Ahmad, Lee Yook Heng

School of Chemical Science and Food Technology

Faculty of Science and Technology

University Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia

 

 

ABSTRACT

 

An equation modeling on Sembulan river, Sabah, Malaysia, has been undertaken using a backward stepwise multiple linear regression.  A good performance has been obtained using a log transformation on water quality data designated as predictors and dependent variable. The regression model is in accordance with the ANOVA result. The temperature, biochemical oxygen demand (BOD), Echerichia Coli, Pb and nitrate were described as continuous predictors, while the river location (downstream, municipal and upstream) was designated as independent string grouping variable, and the chemical oxygen demand (COD) was set up as the dependent variable. The string grouping variable was converted to its dummy variable, which in turn led to design of a three-equation model with respect to river location. The results show that BOD has a strong effect on COD, while Pb and nitrate show less effect on COD. The temperature gives little negative effect on COD, while other variables such as pH, salinity and Cd are excluded from the river modeling since they induce insignificant effects based on backward criterion probability of F-value ≥ 0.100. Using the general linear model with LSD mode, it is revealed that predictor(s) show a remarkable discriminant effect between upstream and municipal/downstream on the 0.05 level. The most effect came from salinity indicated by the canonical discriminant function based on Wilks’ lambda.

 

Keywords:  river modeling; backward stepwise multiple linear regression; water quality.

 

 

ABSTRAK

 

Permodelan persamaan ke atas sungai Sembulan, Sabah, Malaysia, telah dilakukan menggunakan regresi linear berganda langkah demi langkah ke belakang. Prestasi yang menggalakkan telah diperolehi menggunakan transformasi log  ke atas data kualiti air yang digunakan sebagai peramal dan pembolehubah bersandar. Model regresi didapati bersetuju dengan keputusan ANOVA. Suhu, permintaan oksigen biokimia (BOD), Echerichia Coli, Pb dan nitrat telah diperihalkan sebagai peramal selanjar, manakala lokasi sungai (hiliran, perbandaran dan huluan) dinamakan sebagai pembolehubah talian perkumpulan tak bersandar, dan permintaan oksigen kimia (COD) disetkan sebagai pembolehubah bersandar. Pembolehubah talian perkumpulan tak bersandar ditukarkan kepada pembolehubah patung, yang kemudiannya membawa kepada rekabentuk model tiga-persamaan dengan merujuk kepada lokasi sungai. Keputusan menunjukkan BOD mempunyai pengaruh yang kuat ke atas COD, manakala Pb dan nitrat menunjukkan kurang mempengaruhi COD. Suhu memberikan sedikit kesan negative ke atas COD, manakala pembolehubah lain seperti pH, kemasinan dan Cd terkeluar daripada permodelan sungai kerana ia memberikan kesan yang tidak signifikan berdasarkan kebarangkalian ciri ke belakang dengan nilai-F ≥ 0.100. Dengan menggunakan model linear umum dengan mod LSD, peramal didapati menunjukkan kesan pendiskriminasi yang nyata di antara huluan dan perbandaran/hiliran pada aras 0.05. Kesan utama adalah daripada kemasinan seperti ditunjukkan oleh fungsi pendiskriminasi kanonik berdasarkan lambda Wilk.

 

Kata kunci: permodelan sungai; regresi linear berganda langkah demi langkah ke belakang; kualiti air

 

 

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