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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.