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Social Media Based Decision Support Model To Solve Indonesian Waste Management Problem: An Improved Version
Summary
This study used Twitter data and machine learning sentiment analysis to build a decision support model for waste management policy in Indonesia. Social media data can provide real-time insights into public concerns about plastic waste, complementing traditional environmental monitoring data.
Twitter is a commonly used social media and can sometimes picture an entire situation especially environmental issues like waste management. Machine learning and sentiment analysis tools have also been used in many cases around the world and has produced useful results to assist decision making models. In this research Decision Support Model (DSM) and Sentiment Analysis with the help of Naïve Bayes Theorem was used to analyze the waste management case in Indonesia and find out how much improvement is needed in the current situation. The research has found that severe improvements in all of the 5 aspects analyzed is needed to elevate the waste management quality to the next level, especially with a low overall score of 45.29.
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