Extractive Text Summarization for Indonesian News Article Using Ant System Algorithm

The act of simplifying a text from its original source is known as text summarization. Instead of capturing the substance of the original content, an effective summary should be able to convey the information. Recent research on this form of extractive summarization has produced encouraging findings. A graphical model and a modified ant system method will be combined in this literature to provide a solution. The pheromone modification will decide which pertinent phrases will be selected to be a decent summary structure, while the modification process will focus on the point at which the graph construction will be built to represent an article. Additionally, a dataset (Indosum) including news stories that are often utilized in relevant research will be used in accordance to the summary in Indonesian. In addition, the ROUGE approach will be utilized as a tool for evaluation to rate the summary's quality. Finally, this paper concludes with the challenges and future directions of text summarization.