Dress Code Selection Recommender System Based on Smartphone
Abstract
In the era of rapidly developing information technology, the existence of smartphones has become an integral part of everyday life. Appearance and choice of dress code play a crucial role in a person's self-image. Therefore, this research aims to design a smartphone-based dress code selection recommendation system. This system will use clothing usage data, user preferences, and event context to provide relevant dress code recommendations. With this solution, it is hoped that users can easily and efficiently choose the appropriate dress code, increase self-confidence, and create a pleasant dressing experience. This research contributes to the development of smartphone-based applications to support users' lifestyle and personal appearance. This application not only provides dress code inspiration, but also makes it easier for users to make decisions regarding clothing choices. Model testing using Machine Learning with the K-Nearest Neighbor (KNN) algorithm shows satisfactory accuracy, precision and recall, namely 83.67%, 83.82% and 99.34%. This application has the potential to be a useful tool helping users live an informed fashion lifestyle and according to personal preferences, and also minimize the waste of time that would occur when choosing clothes.
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