Implementasi Sistem Rekomendasi Produk di Shopee dengan Logika Fuzzy Berdasarkan Harga, Rating, dan Popularitas Produk

Abstract

A well-prepared abstract enables the reader to identify the basic content of a document quickly and accurately, to determine its relevance to their interests, and thus to decide whether to read the document in its entirety. The Abstract should be informative and completely self-explanatory, provide a clear statement of the problem, the proposed approach or solution, and point out major findings and conclusions. The Abstract should be 150 to 300 words in length. The abstract should be written in the past tense. Standard nomenclature should be used and abbreviations should be avoided. No literature should be cited. The keyword list provides the opportunity to add keywords, used by the indexing and abstracting services, in addition to those already present in the title. Judicious use of keywords may increase the ease with which interested parties can locate our article. Recommender systems play a crucial role in e-commerce by providing relevant product suggestions based on user preferences. One approach that can be used to enhance recommendation quality is fuzzy logic, which enables the system to handle uncertainty in decision-making. This paper proposes the implementation of a product recommendation system on the Shopee e-commerce platform using fuzzy logic, considering three main factors: price, rating, and product popularity. Based on testing and evaluation, the fuzzy logic-based system demonstrates higher accuracy compared to other methods such as collaborative filtering and content-based filtering. The system successfully provides more flexible and relevant recommendations for Shopee users, enhancing their shopping experience.