Abstract

Recommendation systems have now become an important part of a digital service, one example is e-commerce. The facts show that the COVID-19 pandemic has had a significant impact on customers by making them spend more time surfing online to get daily necessities products by shopping on e-commerce sites. With the rapid development of deep learning technology today, of course, it can be used to help in terms of the process of producing a product image-based recommendation system that has a fairly high level of similarity. This study will discuss how to produce an image-based product recommendation system architecture by comparing the results of the application of algorithms 8 pre-trained models that are available and have also been widely used in various studies and the information technology industry. The dataset used is product images sourced from the kalcare.com website. After testing the pre-trained model, then an application prototype was made to be tested then in the final stage of this research a poll was conducted to determine the response and opinion of users to the protopine recommendation system made for e-commerce kalcare.com using deep learning.

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