ANALYSIS OF A DECISION SUPPORT SYSTEM USING AHP FOR FOOD AND RESTAURANT SELECTION BASED ON THE USER’S FOOD CRAVINGS AND LOCATION IN JAKARTA

Abstract

The purpose of this research is to develop a decision support system (DSS) using the AHP algorithm for selecting restaurants based on the user's food cravings and location in Jakarta. The data for the DSS was gathered by scraping restaurant data from online websites. The AHP algorithm implementation was based on the user's criteria, such as food cravings, dietary restrictions, price range, and location. The DSS was then evaluated with users. The findings of the research show that the DSS is effective in helping users make a decision about which restaurant to go to. The DSS was able to take into account the user's criteria and location to generate a list of restaurants that were most likely to meet their criteria. However, the DSS was found to be slow in dealing with large datasets. The conclusion of this paper is that the DSS is a valuable tool for indecisive people who are looking to select a restaurant. The DSS is effective in helping users make a decision based on their criteria and location. However, the DSS is slow in dealing with large datasets. Future research could focus on improving the performance of the DSS for large datasets.