<![CDATA[Indonesia's marine sediment export policy has become a controversial topic among the public, especially in relation to environmental and socio-economic impacts. This research aims to analyze public sentiment towards Indonesia's marine sediment export policy via the X.com platform (formerly Twitter) using Natural Language Processing (NLP) techniques. Data was taken during the period September to October 2024 using the scraping method using the Twitter API. The dataset consisting of 72 tweets was processed through a data preprocessing step to remove irrelevant elements. Sentiment is analyzed using the BERT (Bidirectional Encoder Representations from Transformers) model, which allows deep detection of sentiment context. The analysis results show that 67% of tweets contain negative sentiment, 25% are neutral, and 8% are positive. This finding shows that the public is worried about the impact of marine sediment export policies.]]>
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