Text Summarization of Online News Articles Using the Text Rank Algorithm - Indra Marto Silaban (Asosiasi Perguruan Tinggi Informatika dan Ilmu Komputer (APTIKOM) Provinsi Sumatera Utara, 2024)
Text Summarization in online news media is useful for helping readers to get the essence of a news story. Summarization will be less effective if it is done manually by humans, so we need an application that can do summaries quickly and precisely. By utilizing preprocessing technics with sastrawi python library and the implementation of TextRank algorithm which is part of the extraction method, news that was previously long can be presented in a very concise form. This application is developed using the Python programming language with sastrawi libraries, nltk and StemmerFactory. While the framework used is Django as the backend and bootstrap as the frontend framework.