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- W4200491106 abstract "Within a few months the COVID-19 virus (Corona Virus Disease 2019) spread to all corners of the world including Indonesia. This infectious disease appeared in the city of Wuhan, China at the end of December 2019. In order to prevent all countries from implementing a lockdown policy to fully respect freedom, dignity and human rights, Indonesia is also obliged to prevent the occurrence of a public health emergency that is troubling the world. To avoid public health risk factors, the Central Government and Regional Governments have an important role to carry out health quarantine. The government has the obligation and responsibility to protect public health from this COVID-19 virus. In this paper we are doing a sentiment analysis on the lockdown policy called PPKM (Pemberlakuan Pembatasan Kegiatan Masyarakat, in English: Enforcement of Restrictions on Community Activities) from twitter using Artificial Neural Network (ANN). From the analysis it is found that ANN have the highest AUC score with 95.76 percent. It is also found that neutral sentiment dominating with 48.9 percent while positive sentiment falls second with 28.9 percent and negative sentiments with 22.2 percent. We set the goal for this paper to be able to give an analysis that is beneficial for further research and policy making." @default.
- W4200491106 created "2021-12-31" @default.
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- W4200491106 date "2021-10-06" @default.
- W4200491106 modified "2023-09-30" @default.
- W4200491106 title "Lockdown Countdown: Lockdown Sentiment Analysis on Twitter Using Artificial Neural Network" @default.
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- W4200491106 doi "https://doi.org/10.1109/icodsa53588.2021.9617212" @default.
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