<![CDATA[Indonesia is one of the countries with abundant and stunning natural wealth, making it an ideal tourist destination. As a tourist destination, Indonesia has many hotels, including 5-star hotels, that offer comfort and luxury to tourists. However, with the many choices of 5-star hotels available, prospective visitors often face difficulties in finding a hotel that suits their preferences and needs. The main problem faced is the difficulty in obtaining accurate and reliable information about the facilities, prices, and room availability, as well as the quality of service of these hotels. To address this issue, this research presents a Decision Support System (DSS) that uses the Multi-Objective Optimization by Ratio Analysis (MOORA) method to assist prospective visitors in choosing the best 5-star hotel in Indonesia. This DSS considers various important factors such as location, facilities, price, and customer reviews to provide recommendations that best meet the visitors' needs. The results of the study show that from the 12 hotel data analyzed, the 5-star Hotel Bumi Surabaya City Resort (A10) ranks first with a score of 0.3862. The second rank is occupied by the 5-star Four Seasons Hotel Jakarta (A7) with a score of 0.3241, and the third rank is the 5-star The Ritz-Carlton Bali Hotel (A5) with a score of 0.2987. This DSS is expected to help prospective visitors make smarter and more optimal decisions, thus making their stay more enjoyable and satisfying. This research contributes to providing better and more accurate information for prospective visitors and helps in a more efficient and effective decision-making process. The advantage of this research is that the developed DSS can process data from various sources quickly and accurately, providing recommendations that match user preferences. The MOORA method used has also proven to be effective in filtering the best alternatives based on the specified criteria. However, this research also has several shortcomings, such as the limitation of the data used which only includes 12 hotels, so the results may not be fully representative. In addition, this DSS heavily relies on the quality and accuracy of input data, which can affect the final recommendation results]]>
