FOOD AND BEVERAGE ORDERING SYSTEM USING COLLABORATIVE FILTERING METHOD (CASE STUDY OF PATDUA COFFEE & EATERY)
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Abstract
Patdua Coffee & Eatery is a café that offers a wide variety of menu options, from food to beverages, as well as a comfortable space for customers. However, the absence of a menu recommendation system has led to long queues as customers take a considerable amount of time to make their selections. This research aims to address this issue by developing a website-based ordering system equipped with a recommendation feature using the Item-Based Collaborative Filtering method. The results of the study indicate that the system was successfully implemented and received a very positive response from users. Based on Usability Testing conducted with 32 respondents using a Likert Scale, the system achieved an average score above 3.30 (out of 4) across all aspects, which is interpreted as "Very High." Specifically, the core functionality of the website in providing menu recommendations received a score of 3.47, and the ease of use aspect scored 3.59. Blackbox testing also confirmed that all features operate correctly without any errors found.
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