Implementasi Web Scraping untuk Pengambilan Data Pada Website E-Commerce

  • Apriza Zicka Rizquina Universitas Islam Indonesia
  • Chanifah Indah Ratnasari Universitas Islam Indonesia
Keywords: Web Scraping, E-commerce, Data Mining, HTML Parsing, CSS Selector


Data is a new mind; data is gold; data is a new mine. This is a parable that was as familiar in the digital era as it is today. Data can be utilized, among other things, to improve operational efficiency, spur innovation in a business, understand user needs, and encourage decision-making. Data from e-commerce can be collected in a variety of ways, including web scraping techniques utilizing Python and libraries like Selenium, Beautifulsoup, and Time. The web scraping methods at Shopee and Tokopedia used in this study are HTML Parsing and CSS Selector. This study found that the HTML Parsing and CSS Selector methods cannot be used for web scraping on Shopee owing to bot and CAPTCHA detection mechanisms. However, this method was successfully used on Tokopedia. We conducted 10 web scraping attempts on two product pages, which resulted in around 160–166 data points each time, with 3–18 duplications of data. The average execution time of a program is 1 minute and 0.5 seconds.


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How to Cite
Rizquina, A., & Ratnasari, C. (2023). Implementasi Web Scraping untuk Pengambilan Data Pada Website E-Commerce. Jurnal Teknologi Dan Sistem Informasi Bisnis, 5(4), 377-383.