Multilinear regression analysis on solid waste generation quantity in Malaysia towards sustainable development - Faridah, Zulkipli; Zulkifli, Mohd Nopiah; Noor Ezlin, Ahmad Basri; Cheng, Jack Kie; Siti Sarah, Januri (IASE, 2017)
Inadequate data will affect the efficiency of future planning of solid waste management in order to achieve sustainable development. The purpose of this paper is to investigate the effect of a number of factors, namely GDP, Demand of electricity, Population and Number of Employment, which could be applied to predict the solid waste generation quantities and improve the management of future planning. The data were statistically analyzed by conducting a bivariate analysis and multilinear regression analysis. The results revealed that the GDP, Demand of electricity, Population and Number of Employment reflects the prediction of sustainable solid waste generation. It was found that addition of all predictor variables accounted for 98.9 percent (r = 0.989) changes in the variance in the quantity of solid waste generation. Consequently, the department of solid waste can increase its effectiveness and efficiency in management through the prediction of the quantity of solid waste generation.