Abstract

Indonesia is one of the highest internet users in the world, including in the penetration of information on the internet, online news media. But in general news sites not only display news information, but most sites also display other information such as advertisements and also forms of navigation that interfere with news site readers and interfere with reader’s comfort, from these problems this study aims to implement web scraping techniques with supervised learning methods and analyzing the form of DOM tree and XPath news sites. The supervised learning approach method is the method used in this study, which is one of the methods of machine learning. By combining these web scraping techniques with supervised learning, the aim is to be able to implement and optimize web scraping techniques to gather news information from various sites. To do basic web scraping namely knowing DOM patterns, XPath structure as a data model or selector at each site. The results of research in the form of a web scrap application that can retrieve news site content without copy paste and the data is stored in a database and displayed to the user application form for the reader without any ads and navigation that disturb the reader.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.