AHP and GRA-Based Decision Support Model for Classified Ad Websites: A Case Study on Vehicle Selection

This study proposes an application for scoring and ranking vehicles selected from classified ads based on criteria defined by decision-makers. The approach aims to reduce the time wasted in commonly encountered decision-making situations. The criteria weights were determined using the Analytic Hierarchy Process based on relative comparison data separately defined by two decision-makers. The degree and ranking data for the alternatives were obtained through Grey Relational Analysis. For Decision Maker A, the highest-ranking vehicle was a hybrid car with a C-segment, sedan body type, automatic transmission, and a 1.8-liter engine capacity, scoring 91%. For Decision Maker B, the result was a D-segment vehicle with a sedan body type, automatic transmission, and a 1.5-liter engine capacity, ranking first with 85%. In situations where the comparison matrix could not be completed due to time constraints, an analysis based on the assumption of equal weights indicated that the hybrid car with a C-segment, sedan body type, automatic transmission, and a 1.8-liter engine capacity ranked first with a Grey Relational Degree of 81%.