Comparison Of CNN And LSTM Strategies For Estimation Investigation Of IKN Relocation
Keywords:
National Capital, Sentiment Analysis, CNN, LSTMAbstract
As time progresses, information technology has begun to reshape the forms and patterns of communication within society. Social media is one of the services that currently enables more open communication in political and social interactions within communities and nations. A prominent theme in domestic politics is the plan to relocate the nation’s capital, which has become a widely discussed topic. The purpose of this research is to understand and analyze public responses captured in comments on YouTube videos related to the issue of relocating the capital city. Additionally, this study aims to evaluate the correlation between two algorithms, CNN and LSTM, in analyzing public sentiment regarding the capital relocation. The data was collected from videos on the capital relocation along with 11,000 comments. After testing, the CNN model achieved an accuracy of 0.975, while the LSTM model achieved an accuracy of 0.966. The analysis revealed both positive and negative sentiments regarding the capital relocation plan. The findings of this research provide policymakers with a more detailed understanding of public perspectives on the capital relocation and demonstrate the benefits of these two algorithms in analyzing textual data with unstructured information.
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