Sistem Pengecekan Toko Online Asli atau Dropship pada Shopee Menggunakan Algoritma Breadth First Search

Abstract

The abundance of online shops on web ecommerce Shopee's makes it difficult for consumers to detect the genuineness of an online store. Online store detection app is an application to detect genuine online shop, good rating online shop, and fake online shop, which is useful as a recommendation to consumers in buying a product against an online shop. Detection by implementing the Breadth First Search (BFS) algorithm with Web Scraping techniques against Web e-commerce Shopee with the keyword "Kemeja Pria" with a search number of 5000, generate 1389 online shops data with the detection results of genuine online shop, good rating online shop, and fake online shop respectively as many as 90 online shops (6.5%), 948 online shops (68.3%), and 351 online shops (25.3%). The time it takes for the system to visit each node, from the first node to the 1389 node by applying the Breadth First Search algorithm takes about 2,690,021 second, or about 44.833683333 minutes, with the queue formation process, node browsing, online shop detection, and test results. The results reveal that the Breadth First Search algorithm is a simple algorithm that can be used to perform online store detection with good performance.

Keywords

• online shop, bfs, web scraping, e-commerce, shopee