EatPlace: restaurant and café recommender system for tourist / Ahmad Tasnim Muhamad Azlan

Food tourism describes activities that allow visitors to try food and drinks that are unique to culture of certain ethnic or race. It includes values of the food to the history, culture and the environment of the country as well as tasting food and drink from different regions of the world. Recommender systems in this project, programmes that provide recommendations to users based on a set of criteria in finding restaurant or café. Tourist keep continue facing difficulty to decide where they wanted to have a meal in a foreign country. Therefore, this project aims to develop mobile application EatPlace: Restaurant and café recommendation system for tourist and evaluate the mobile application using functionality testing and user acceptance test. The location of the study focused on North-East district, Penang. The method used in this project is content based filtering for the recommender system in finding restaurant and café. It is a sort of recommender system that makes predictions what user would like based on past activity. Through the analysis of UAT, this project achieve objective and most participant would prefer using mobile application integrated with Google Maps to recommend a restaurant and café based on filtering preference than opening a browser to type and search a place to eat as tourist. Future recommendation for this project would have filters for halal and non-halal food and easier for Muslim users to identify the status of the restaurant.