Predicting Consumer Interest in All You Can Eat Restaurants with Gradient Boosting Algorithm

Abstract

The rise of businesses in the food industry makes industry players think creatively. One of the trends in this industry is the “All You Can Eat” restaurant with its various variations. This type of restaurant is considered capable of being an attraction for consumers because consumers can eat every dish as much as they want without a limit on the amount. However, it is difficult to map out the factors that make consumers want to come back to the restaurant. This research will build a web application with machine learning features using the Gradient Boosting algorithm that can map whether consumers will come back or not, so that restaurant businesses can use this application to continuously improve the performance of their restaurants.