An application of multiple regression for predicting Turbidity of standard water quality for industrial and household consumption

Abstract

Received: 15 September 2021 Revision: 14 Oktober 2021 Accepted: 16 Oktober 2021 A multiple regression approach was applied in this study with the aim of predicting Turbidity value of standard water in water treatment plant. Turbidity is a level of cloudiness in water due to the presence of particles or microorganisms. Turbidity in standard water did not affect human health in term of hazardous, even though it represent of poor quality water. Water treatment plant reduce the cloudiness in water by applying chlorination process. There are three independent variables of water quality involved to predict turbidity value. They are PH, color-spectrum and electrical conductivity. The correlation among variables were checked before conducting multiple regression. Color-spectrum has the highest correlation with the turbidity. The stepwise approach remain two independent variables involved in multiple regression equation, color-spectrum and electrical conductivity with the value of R-square equal to 0,97. Meaning that the two variables has the ability of explaining variances in turbidity up to 97 %.