Implementasi Sistem Aplikasi Pemesanan Aksesori Baliem Menggunakan Algoritma Collaborative Filtering
DOI:
https://doi.org/10.30865/klik.v3i6.965Keywords:
E-commerece; Mobile Application; Model View Presenter; Collaborative Filtering; Item BasedAbstract
Warpitong application is an online sales application that contains information about baliem cultural accessories products. In the application users can make transactions, contact sellers and more. The power of online business lies in its unlimited suggestions. Unlimited means covering not only one region or demographic group, but also all groups in society at large. Anyone connected to the Internet is a potential market. This can be seen from the number of online stores that continue to emerge and increase every year, both on a small scale and nationally, even international standard online stores. Therefore, it is necessary to develop a system for the purchasing system, the purpose of which is that the new system developed can solve problems and help manage information, so that the information produced is more accountable and responsible. To achieve this goal requires precise methods such as using Model view presenter (MVP) and Collaborative filtering algorithms. The model view presenter (MVP) is a derivative of the model view controller (MVC) architecture pattern, and is mostly used to build user interfaces, while collaborative filtering algorithms aim to prioritize different customer and customer reviews with testimonials. Based on the results of whitebox testing, testers can submit program testing to the remommed item program once. The purpose of the Collaborative Filtering algorithm in this study is to provide product recommendations to buyer users who have not seen similar products, prices and categories but there is no choice determined by the buyer user. Based on previous interests from users who have similar interests. From the results of using this technique to determine recommendations, products, prices and categories in the warpitong application, based on the Collaborative Filtering algorithm using an item-based system
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