<![CDATA[Waste management remains one of the major challenges in achieving sustainable development, where the success of waste management programs is highly dependent on public awareness and participation. With the rapid growth of social media usage, public conversations generated on digital platforms provide valuable insights into community perceptions regarding environmental issues. This study aims to analyze public awareness of waste management programs by integrating IndoBERT-based Sentiment Analysis and BERTopic-based Topic Modeling on Indonesian social media data. Data were collected from the X (Twitter) platform using waste-management-related keywords and processed through several preprocessing stages, including text cleaning, tokenization, stopword removal, and normalization. The sentiment analysis results demonstrate that the IndoBERT model achieved an accuracy of 93.82%, with sentiment distribution consisting of 44.88% positive, 29.84% neutral, and 25.28% negative sentiments. Furthermore, BERTopic successfully identified five dominant discussion topics, namely waste banks, recycling, temporary and final disposal sites (TPS and TPA), urban sanitation facilities, and environmental education. The integration of sentiment and topic analysis produced an Awareness Index score of 0.694, which falls into the high-awareness category. The findings indicate that Indonesian society generally demonstrates a positive perception and a relatively high level of awareness toward waste management programs, although concerns regarding operational services and waste management infrastructure remain evident. This study contributes a novel approach by combining IndoBERT, BERTopic, and an Awareness Index framework to provide a comprehensive assessment of public awareness based on social media analytics, which can support evidence-based policymaking and sustainable waste management strategies.]]>
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