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Astri Pertiwi
Agung Triayudi
Endah Tri Esti Handayani


Social media platforms and micro blogging websites are rich sources of user-generated data. The internet has changed the way people express their thoughts and feelings through social media, like Twitter. Twitter as a place for information flow, Twitter is a rich source for learning about people's opinions and sentiment analysis. This study aims to determine how much the impact of the co-19 pandemic on economic conditions in Indonesia, measured from the resulting community sentiment. To solve the problem in this case study using a method that is for pre-processing data using cleansing, filtering, tokenization and stemming. The classification process uses the Artificial Neural Networks (ANN) method. The data used are Indonesian-language tweets with the keywords Covid-19, Economi Indonesia, MSME, storylineverline and phk, with a dataset of 1600 tweets. The results of this study are sentiment analysis of the impact of co-19 on the Indonesian economy. Results of training dataSMEs get an accuracy of 99.37% and Ojekonline data get an accuracy of 99.25%.


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Pertiwi, A., Triayudi, A. and Handayani, E. T. E. (2020) “Sentiment Analysis of the Impact of Covid-19 on Indonesia’s Economy through Social Media Using the ANN Method: Sentiment Analysis of the Impact of Covid-19 on Indonesia’s Economy through Social Media Using the ANN Method”, Jurnal Mantik, 4(1), pp. 605-612. Available at: (Accessed: 13August2022).
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