Aroma Atlas: a mobile application for personalized recommendation café finder using global positioning system

In the current digitalized world, coffee lovers want to have more than a caffeine dose, they want to have an individualized, convenient, and interactive experience when exploring cafes. Nevertheless, most of the current applications do not provide any significant customization, multi-vendor, and filtering. The proposed project introduces Aroma Atlas, a mobile application developed using Android Studio, that designed to help users find cafes based on their current GPS location, preferred drink types and coffee bean choices, while also offering role-based functions for customers, business owners and administrator. Firebase was used to develop the system as a real-time cloud database and Google Maps API to provide location services. The process of development was based on the Agile Scrum methodology, which made it possible to implement, test, and improve features iteratively. The most important modules are user registration and log-in, discovery and filtering of cafes, personalized recommendations of cafes, rating and reviews, booking and order management, a dashboard of the business owner, and an admin panel with approval and analytics on the web. The System Usability Scale (SUS) and User Acceptance Testing (UAT) were used to evaluate the system. The findings proved to be very usable, user-satisfying, and reliable in terms of functionality. Even though the system is confined to the Machang, Kelantan region and has not yet implemented machine learning or loyalty rewards, the project is effective in achieving its goals and is the basis of future improvements, including the expansion of coverage to other locations, the development of smart recommendations, and publishing to app stores. Aroma Atlas eventually closes the gap between the users and the independent cafes and facilitates a smarter and more fun experience of finding cafes.