A COMPARATIVE ANALYSIS OF SIMPLE ADDITIVE WEIGHTING, WEIGHTED PRODUCT, AND SIMPLE MULTI-ATTRIBUTE RATING TECHNIQUES FOR SELECTING TOURIST DESTINATIONS (A CASE STUDY IN MAGELANG REGENCY)

Abstract

The large number of tourist destinations in Magelang Regency forces tourists to choose which destinations they will visit. The numerous criteria in selecting tourist destinations makes it increasingly difficult for tourists to determine which destinations they will visit. Therefore, a decision support system is needed to help tourists more effectively and efficiently in determining which tourist destinations they will visit. This study uses the Weighted Product (WP), Simple Additive Weighting (SAW), and Simple Multi-Attribute Rating Technique (SMART) methods. These three methods are then compared to determine which method is most appropriate. SAW, WP, and SMART produce identical rankings between methods, indicating consistent modeling quality. This consistency strengthens the validity of the decision results. From the comparison between the SAW, WP, and SMART methods, the total percentage of the SAW method is 99.9934%, greater than the WP and SMART methods with a percentage of 99.9933%. This shows that the data structure, criteria weights, and value ranges between alternatives are relatively uniform, so that the linear (SAW), geometric (WP), and utility-based (SMART) methods produce equivalent decision patterns to solve the problem of determining tourist destinations in Magelang