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Journal : Building of Informatics, Technology and Science

Side Dish Store Recommendation System Utilizes A Collaborative Filtering Methodology Suryani, Suryani; W Soetikno, Y Johny; Octavianus, Michael; Faizal, Faizal; Hasriani, Hasriani; Nurdiansah, Nurdiansah; Bahtiar, Akbar
Building of Informatics, Technology and Science (BITS) Vol 6 No 1 (2024): June 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i1.5229

Abstract

Side Dish Stores serve as traditional venues for buying and selling a diverse array of products, including fish, foodstuffs, beverages, kitchen spices, clothing, souvenirs, and more. In their pursuit of maximizing profits, traders use competitive strategies, such as online marketing, to expand their sales channels and promote products digitally. This research aims to generate recommendations for selling fish, and traditional supermarkets through a collaborative filtering method. The criteria used to generate recommendations for shops or fish sellers among 25 alternatives include product type, availability, service quality, shop cleanliness, product quality, and sales volume. The research results indicate that the highest predicted value is 0.70, where user 16 exhibits the highest similarity with user 14. Consequently, TSF 1= 4.17, TSF 5= 3.5, TSF 9= 3.33, TSF 13= 3.83, and TSF 15= 4.5. When ranked, TSF 15 will be the first recommendation for user 16, followed by TSF 1, TSF 13, TSF 5, and TSF 9. This recommendation system facilitates consumers in determining the appropriate shop or fish seller to visit when shopping at the Side Dish Store. Traders can easily market products to enhance sales. Moreover, the system streamlines buying and selling transactions for traders and consumers without the necessity of direct visits to the Side Dish Store