Travel Budget Prediction for Determining Tourism Objects Using Simple Additive Weighting (SAW) Algorithm

Predicting tourism cost planning is one of the most exciting activities to do before traveling, so that travel activities do not affect financial stability. On the one hand, the budget can be used as a reference for planning tours. Making an application to estimate or determine the selection of tours based on the budget for travel costs is not easy to do and requires consideration of several factors and involves a calculation process. In this study, determining tourist locations based on the travel budget was carried out by implementing a decision support system using the Simple Additive Weighting (SAW) method. The SAW algorithm is used in this study because it can provide an alternative prediction of tourist destination locations as the best trip based on ranking existing budget information. The experimental results in the study show that the SAW method uses three parameters (total budget costs, vacation duration, and the number of people) and a filtering process (filtering) on the budget data that has been stored based on the parameters of tourist destinations.