Analisis Sentimen terhadap Penanggulangan Bencana di Indonesia
DOI:
https://doi.org/10.30646/sinus.v19i2.563Keywords:
sentiment analysis, python, text mining, twitter, bpbdAbstract
Disasters have become a part of human life, whether natural disaster, non-natural disaster or from human error, which is causes fatalities, environmental damages, property losses, or psychological impact, especially in Indonesia. The National Agency for Disaster Countermeasure (BNPB) is the Indonesian board for natural disaster affairs. For each region, Badan Penanggulangan Bencana Daerah (BPBD) as for as the regional disaster management. Social media has become a part of everyday life for people nowdays. The purpose of this research is to find out the public reaction, with classification positive, neutral or negative opinion to the disaster management in Indonesia from Twitter. One text mining method from Natural Processing Language (NLP) is sentiment analysis. Sentiment analysis applied to analyze data with public opinion as the decision-making support. Based on the research, there were 23,53 % positive tweets, 57,35 % neutral tweets and 19,12 % negative tweets. From the result, mostly Indonesian have neutral opinion about the disaster management. The result also displayed in histogram, pie chart and word cloud.References
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