<![CDATA[As one of the latest innovations in Indonesia, the launch of Danantara has attracted public attention, especially the X (formerly Twitter) social media community. Understanding public sentiment about the launch is crucial due to the varied reactions. Using the Support Vector Machine (SVM) method as the primary classification algorithm, this study aims to examine how Indonesians perceive the launch of Danantara. Data collected through scraping techniques from social media posts were then processed through text preprocessing processes such as data cleaning, tokenization, and normalization. Categorizing sentiment into positive, negative, or neutral can be done using the signal variable model (SVM). The results show that the majority of the public has a certain sentiment towards the launch of Danantara, as the SVM model can classify sentiment very accurately. In the future, this study will help stakeholders understand public opinion and create better communication plans.]]>
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