Adzlani, Nasri (2021) Klasifikasi Analisis Sentimen Terhadap Covid-19 Menggunakan Naive Bayes Classifier. Tugas Akhir thesis, University of Technology Yogyakarta.
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Abstract
BAB VII ABSTRACT Indonesia has become one of the countries with a high number of active twitter users. Twitter can be used as material for sentiment analysis on the topic of Covid-19. Sentiment analysis is a branch of text mining with a classification process on documents or texts. This research was conducted to find out how to analyze public sentiment on tweets and retweets which will produce positive, negative and neutral retweet tweets and presentations so that we can find out how the impact of the corona virus in Indonesia according to public opinion on Twitter. Retrieval of tweet data from twitter is done using the Tweepy library and with the Twitter API, to gain access to the Twitter API you must first register with Twitter Developer which generates 1,200 training data and 300 test data. The data obtained then entered into preprocessing with the stages of casefolding, regular expression, stemming, stopword and tokenization. The results of this study indicate an accuracy value of 88% with a total accuracy of positive 93%, negative 98% and neutral 73%. Keywords: covid, sentiment, corona
| Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
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| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Sains Dan Teknologi > S1 Informatika |
| Depositing User: | Kaprodi S1 Informatika UTY |
| Date Deposited: | 27 Mar 2021 01:19 |
| Last Modified: | 27 Mar 2021 01:19 |
| URI: | http://eprints.uty.ac.id/id/eprint/7179 |
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