Design and Development of a Web-Based Decision Support System for Used Car Selection Using Simple Additive Weighting Method to Provide Accurate and Fast Recommendations for Showroom Customers

Abstract

The selection of used cars to choose from can be overwhelming for potential buyers, and the variables, like price, engine specifications and production year, are quite complex. This study develops a DSS in the form of a web-based application designed for fast and accurate recommendations regarding vehicle selection. They use the Simple Additive Weighting (SAW) method, which calculates the total of performance ratings given to each alternative over multiple criteria to find the best option for decision-making. The development proceeds with the Waterfall model, which includes requirements analysis, system design (DFD and ERD), implementation (PHP and MySQL), and functional testing (Black Box). The decision process considers seven parameters Brand, Price, Engine Specs, Transmission, Mileage, Description and Year of Production. Results show that the system generates a preferred order of the car options, assigning these criteria different levels into specific priority weight values that ease the buyer in choosing their ultimate car choice. This application will be important as a tool to raise efficiency and accuracy of selection in used car showrooms by bridging the knowledge gap between customers.