Rancang Bangun Sistem Rekomendasi Komponen Komputer Menggunakan Metode Item Based Collaborative Filtering Berbasis Web
Keywords:
Personal Computer Components, Item Based Collaborative Filtering, Blackbox TestingAbstract
When you want to buy a PC component, there is a problem in the form of matching the price with the quality of the components and the average person doesn't know how to choose a good component between one component and another. From the problems that have been mentioned, it is therefore necessary to have a recommendation system that can provide input or Personal Computer recommendations based on needs and interests in finding references. The Item-Based Collaborative Filtering technique is an algorithm that can be used to suggest the selection of components for personal computers. The item-based collaborative filtering method also has advantages, one of which is the ability to filter data and view existing data, one of which can be generated through the history of user choices. Selection of personal computers through applying the Item-Based Collaborative Filtering approach can produce recommendations in the form of PC components through the process of selecting categories and price ranges inputted by the user. The application that has been made has been tested using the blackbox method and manual calculation testing and has obtained the result that by blackbox testing the system has no errors and is as expected, then by testing manual calculations to get results, namely manual calculations with calculations on the system have obtained the same results . So after this research is done, there are suggestions for developing, namely the method or algorithm used in this study can be combined with other algorithms, so as to produce even better recommendations and can provide recommendations to users who have never owned a PC component and add API for PC components list, so no need for manual input on the components menu in the admin.
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