<![CDATA[Food ordering apps are playing an increasingly important role in allowing users to easily and efficiently order food at various restaurants. However, users are often faced with confusion when choosing a menu that matches their preferences. With the aim of improving user experience and facilitating the decision-making process, this study introduces an approach that uses the Analytical Hierarchy Process (AHP) to provide personalized menu recommendations to food ordering app users. The AHP method is used to develop a ranking that considers various factors related to user preferences, including taste, value and budget. App users have the ability determine of each these factors varies based on the context and specific circumtances, which is then used in the ranking calculation. The model was implemented and tested using real user data. Preliminary experimental results show that users using the AHP-based menu recommendation system are more likely to order dishes that match their personal preferences. This research has practical significance in developing food ordering applications that are more intuitive and in line with user needs. By using AHP to provide personalized menu recommendations. This app has the potential to increase order conversion, build customer loyalty, and reduce food waste. In addition, this research also provides insight into how ranking techniques.]]>
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