In modern days, online shopping is inevitable for varies types of customers around the world to shop at ease. However, online shopping is not always favorable as there are few obstacles that customers may face while doing online shopping. Therefore, the above-said predicaments must be carried out. When comes to purchasing the correct size of garments online, it is a prominent drawback for shopping online and it is an unfortunate for the customers to get the correct size of the garments before purchasing online because they don't have the chance to try it on. This research proposes a recommender system based on Fuzzy Logic Controller with the function of predicting and selecting the most suitable clothing size for a specific customer that used to be an online shopper to improve online shopping advantages. There are total of five body properties for male t-shirt (neck, shoulder, sleeve, chest and waist in cm) from five different sizes. The body size measurements from Uniqlo were used as a reference in this research and stored in a database. For the experiments, total of 7 male students, between the ages of 20 - 25 were selected and measured individually to collect. The output of this findings is the most appropriate size for the customer with high degree of fitness. The size classification allows customers to know their body size whether it is "extra-small", "small", "medium", "large" or "extra- large".
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