DEVELOPMENT OF WEB SCRAPING APPLICATION FOR E-COMMERCE PRODUCT PRICE DATA COLLECTION USING PYTHON (CASE STUDY: TOKOPEDIA)

Abstract

Development of a web scraping application system for collecting e-commerce product price data using Python designed to automatically retrieve product data from the Tokopedia e-commerce platform in order to help sellers prepare sales strategies and market competition which usually require excessive time and resources. A sales strategy is a guideline for seeking innovation to run a business, and can determine benchmarks for success as a seller. This research aims to design a system that is able to work automatically and efficiently to provide accurate data and help sellers to analyze market conditions. The design of this system was carried out using the waterfall development method and using the Python as a programming language. The results of this research will provide accurate data and a dashboard that helps sellers analyze the market from the Tokopedia platform. Application testing also ensures that it has been carried out for accurate knowledge and that the resulting application is more user friendly and the resulting system meets the existing flexibility criteria. The results of all these tests also can be concluded that the resulting application is quite good although there is still a lot of development needed in terms of processing speed and analysis results displayed on the dashboard.