Currently, various types of news media that are developing have their own challenges, one of them is the increasing number of digital or online media. The increasing number of digital media in the form of online news sites not only has a positive impact on society, but also poses challenges. The more the number of online news portals increases, the more information is spread out. With a variety of topics and diverse information, it creates problems for readers to make time efficient in reading in full to obtain the desired information. This makes the phenomenon of text summarization very important. The purpose of this study is to analyze the Latent Semantic Analysis method in the text summarization process. The dataset used comes from previous research which includes 100 Indonesian news articles from various online news portals. In the experiment process, the Steinberger and Jezek techniques are used for the sentence selection process. The summary process is carried out using three types of compression rates, namely 10%, 30% and 50%. The best results obtained in this study are the precision value of 20% at a 10% compression rate, a recall value of 42% at a 50% compression rate, and an f-measure value of 22% at a 50% compression rate.