Decision Support System for Subsidized Housing Selection Based on Best-Worst Method and Simple Additive Weighting

Abstract

The increase in population and urbanization in Indonesia has led to a large demand for housing supply in cities, but the increase has not been matched by an increase in population welfare, so the Government offers subsidies for household loans to Indonesian citizens through household loan credit (KPR). The selection of subsidized housing that meets the criteria desired by the people is not a simple problem because of the many choices of subsidized housing with relatively similar prices and limited information that is owned by the general public. Therefore, this research will fulfill the wishes of the people through the development of a decision support system (DSS) for the selection of subsidized housing that uses the Best-Worst Method (BWM) and the Simple Additive Weighting (SAW) approaches. The results of testing in this study have provided adecision support system for subsidized housing that is most following the wishes of the person. This decision supportsystem also makes it easier for the person to select subsidized housing so that low-income persons can avoid making mistakes in choosing the subsidized housing they must pay within the next 15-20 years.