TO STUDY THE SINGLE ORDER OF MULTIPLE REGRESSION MODEL OF WATER QUALITY INDEX (WQI) IN MANJUNG RIVER AND ITS TRIBUTARIES

Abstract

This research highlights a multi-variety technique to examine the relationship between dependent and independent variable in forecasting the water quality index in Manjung Rivers and its tributaries. Multiple regression statistical method been used to predict the water quality as the prediction is more accurate and able to be understood by the public. The model building process been used to analyse and generate the data. There are 4 phases under model building process and we need to run all the possible models for each phase. For phase 1, there are 63 possible models. The number of possible model started to reduce as we started to eliminate insignificant variable in phase 2. Then, this model then needs to run under eight selection criteria to identify the best model for phase 3. Lastly, for phase 4 we need to identify the randomness and normality of the data. After that, we need to verify the validity of our best model by using Mean absolute percentage error (MAPE). According to Lewis's (1982) interpretation of MAPE results is a means to judge the accuracy of the forecast as less than 10% is a highly accurate forecast, 11% to 20% is a good forecast, 21% to 50% is a reasonable forecast, and 51% or more is an inaccurate forecast. Lastly, we able to identify the main parameters that give a significant contribution to the water quality index and we able to generate a new equation in forecasting the water quality by using the significant elements only.