Hybrid Recommendation System with Clustering and Classification Method Based on Case of Clinic XYZ

Abstract

With the development of IT systems in many areas, all data that generated hold potential value that waiting to be unlock, one way is to do product recommendation system based on it. Clinic XYZ is one of the largest beauty aesthetic services in Indonesia. After implementing its ERP systems, Clinic XYZ wants to gain more benefit by doing cross sell of their product to existing customer. Product recommendations system is the solution that developed for it. Product recommendation system is an information-filtering system that handles overload of information and give a recommendation to user a recommendation-based preference, interest of user behavior that observed form those data. The common use algorithm for product recommendation system is collaborative filtering and done directly to whole data. This research applies 2 steps of algorithm, clustering, to separate the customer into different cluster based on the master data that available and classification to each cluster for product recommendation in the clinic to the existing customer. The result show that the 2 steps method generate better result. © 2020, World Academy of Research in Science and Engineering. All rights reserved.