2022
DOI: 10.30865/mib.v6i4.4549
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Food and Beverage Recommendation in EatAja Application Using the Alternating Least Square Method Recommender System

Abstract: EatAja is a startup in Indonesia that provides a mobile application-based food and beverage ordering solution for restaurants. The EatAja application uses transaction data to recommend food and beverage menus to customers. Previous studies have developed recommender systems using the Apriori and Collaborative Filtering methods. However, there are shortcomings in the recommendation system using both methods, i.e., the lack of personalization factors and low scalability. The learning method with matrix factoriza… Show more

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