Sosial Media Analisis Berbasis NLP Untuk Mempercepat Tanggap Bencana Banjir

Flood disasters that are monitored in real-time on social media can be seen to report directly the condition of affected areas. Areas have been warned by floods were informed via media. Surrounding areas likely more vigilant speeding up information and getting responses from users who around flood-prone The research aims provide visualization models accelerate flood response disaster management, track with increasing vigilance, recovery analysis approach used Natural Language Processing (NLP), a data source derived posts Instagram is taken for analytical materials. Data sources hashtags Kalimantan using (NLP) process stage get core visualizations speed information. Visualization based extracting posts, responses, provides troubleshooting importance results increase awareness surrounding area floods, it amount hashtag accelerating management tracking recovery.