E-Commerce Web Design at XYZ Store with Recommendation System Features

Abstract

This research aims to design and implement a web-based e-commerce system for XYZ Store by providing a fresh vegetable product recommendation feature, using the Apriori algorithm and the Rapid Application Development (RAD) approach. The design process begins with collecting data through interviews to find out the needs of the system. Transaction data for one month was analyzed using the Apriori algorithm to identify patterns of association between products that are often purchased together. The results of this analysis were used as the basis for creating recommendation features. The RAD approach was used because it allows the system to be developed quickly and gradually by involving users in each phase of development. This research analyzes the usability level of the platform using the System Usability Scale (SUS) method. Testing was conducted on 15 participants who had tried the platform prototype in the designed usage scenario. The measurement results indicate that the average SUS score is 78.2, placing it in the “Good” category. The recommendation system feature received a positive response, with the majority of users finding it helpful in finding relevant products. These findings suggest that integrating the recommendation system not only enriches the platform's features but also contributes to improving the overall user experience.