1. What is the method used in this research?
The method used in this research is a qualitative research method. It produces descriptive data in speech or writing from observed things. Data collection can involve asking users to rate, rank, choose, or list items. A recommendation system, based on content-based filtering, recommends items similar to previously liked items. It uses data mining techniques and algorithms to identify user preferences. The method focuses on analyzing content descriptions and user-item interactions, considering user profiles and product features. Users can select features or have them identified by developers. Similarities between products and user interests are calculated using the dot product method. The method has limitations, as recommendations are limited to similar items, missing out on unexpected items.
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2. What is the principle of content-based filtering?
Content-based filtering is a recommendation method that provides suggestions based on the similarity of item profiles. After preprocessing, profile items are compared to identify similarities. This method analyzes content consumed by users, such as genre, author, or artist, and matches them with similar content to generate relevant recommendations. It allows for high personalization, increases user satisfaction, and engagement, and does not require data from other users or user behavior information. Content-based filtering is easier to implement and scale, making it efficient in handling large volumes of data.
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3. How does the recommendation system benefit Mubtada Kopi visitors?
The recommendation system benefits Mubtada Kopi visitors by eliminating the over-choice phenomenon, allowing them to choose their preferences easily. It also reduces the time needed to order drinks, as the application is built to be user-friendly. Baristas can focus on their job, making drinks without having to provide recommendations, while customers still receive personalized suggestions from the system. The Content-based filtering method recommends rosella tea, chocolate, lemon tea, blossom tea, and spice tea, enhancing the overall customer experience.
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