CLOTHING PRODUCT SELECTION RECOMMENDATION SYSTEM WITH KNOWLEDGE BASED RECOMMENDATION METHOD
Keywords:
clothing, knowledge, RAD, recommendations, systemAbstract
The market which is the largest wholesaler of clothing in Central Java is the Klewer market area and its surroundings. One of the clothing stores in the area is the Simple Inc Store. Simple Inc Store is a large kiosk that sells clothing products in the form of various types of shirts, t-shirts, jackets, sweaters and pants. Sales of products in these stores are still done conventionally, namely customers come directly to the store to choose and buy products. The number of clothing products that are sold makes customers experience difficulties in the process of selecting clothing products. Therefore, it is necessary to develop a recommendation system that can assist customers in choosing clothing products. The purpose of this study is to build a Recommendation System for Selection of Clothing Products by applying the Knowledge Based Recommendation method. The research method used in this research is Rapid Application Development (RAD) which consists of 5 stages, namely Business Modeling, Data Modeling, Process Modeling, Application Generation, and Testing. Knowledge based recommendation has the advantage of being able to set the level of user priority based on the user's needs for the product. Knowledge based recommendation on the recommendation system for the selection of clothing products can provide 5 choices of search attributes for clothing products, namely brand, price, material, color and size. clothing product selection recommendation system can display clothing product information, perform clothing searches based on customer needs based on a choice of 5 attributes and can display clothing product recommendations. Clothing products with the highest similarity value are displayed as clothing product recommendations. The results of the system testing using the blackbox testing method show that the functions in the recommendation system for selecting clothing products have successfully run as expected.
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