Aziz Musthafa, Tri Harmini, A. Setiawan, Nur Aini Shofiya Asy’ari
{"title":"情绪分析——印尼社会对抗奥密克戎病毒的朴素贝叶斯方法","authors":"Aziz Musthafa, Tri Harmini, A. Setiawan, Nur Aini Shofiya Asy’ari","doi":"10.21111/fij.v7i2.9359","DOIUrl":null,"url":null,"abstract":"[Analysis Of News Sentiment And Public Opinion On Omicron Virus In Indonesia Using The Naïve Bayes Method] The Covid-19 virus continues to mutate to form new variants. The last detected variant, the Omicron variant, is known as the B.1.1.529 variant. This variant was first reported from South Africa on 24 November 2021 and has now spread worldwide. In July 2022 Omicron cases experienced a spike. This has led to a lot of public opinion, especially on social media, about the omicron virus. This study aims to classify public opinion on the emergence of the Omicron virus on Twitter and YouTube social media into positive, negative and neutral classes. The method used in this study is the naïve Bayes algorithm. Naïve Bayes is a method that can be used to classify public opinion sentiment. The results of sentiment analysis research using naïve Bayes produce an accuracy rate of 0.82%. Then the model was tested to read public opinion on Twitter from 5 October 2022 to 27 October 2022. The results for Twitter user sentiment on the keyword Covid 19 were dominated by positive sentiment with a percentage of 85%. And sentiment with the keyword Omicron is still dominated by positive sentiment with a percentage of 49%. It was stated that the results of the classification on data for October 2022 meant that people were much more optimistic about the disappearance of the Omicron virus. Henceforth this research can be improved by adding data or using a different algorithm or implementing an existing algorithm","PeriodicalId":33722,"journal":{"name":"Fountain of Informatics Journal","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analisis Sentimen Opini Masyarakat Terhadap Virus Omicron Di Indonesia Menggunakan Metode Naïve Bayes\",\"authors\":\"Aziz Musthafa, Tri Harmini, A. Setiawan, Nur Aini Shofiya Asy’ari\",\"doi\":\"10.21111/fij.v7i2.9359\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"[Analysis Of News Sentiment And Public Opinion On Omicron Virus In Indonesia Using The Naïve Bayes Method] The Covid-19 virus continues to mutate to form new variants. The last detected variant, the Omicron variant, is known as the B.1.1.529 variant. This variant was first reported from South Africa on 24 November 2021 and has now spread worldwide. In July 2022 Omicron cases experienced a spike. This has led to a lot of public opinion, especially on social media, about the omicron virus. This study aims to classify public opinion on the emergence of the Omicron virus on Twitter and YouTube social media into positive, negative and neutral classes. The method used in this study is the naïve Bayes algorithm. Naïve Bayes is a method that can be used to classify public opinion sentiment. The results of sentiment analysis research using naïve Bayes produce an accuracy rate of 0.82%. Then the model was tested to read public opinion on Twitter from 5 October 2022 to 27 October 2022. The results for Twitter user sentiment on the keyword Covid 19 were dominated by positive sentiment with a percentage of 85%. And sentiment with the keyword Omicron is still dominated by positive sentiment with a percentage of 49%. It was stated that the results of the classification on data for October 2022 meant that people were much more optimistic about the disappearance of the Omicron virus. Henceforth this research can be improved by adding data or using a different algorithm or implementing an existing algorithm\",\"PeriodicalId\":33722,\"journal\":{\"name\":\"Fountain of Informatics Journal\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Fountain of Informatics Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21111/fij.v7i2.9359\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fountain of Informatics Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21111/fij.v7i2.9359","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analisis Sentimen Opini Masyarakat Terhadap Virus Omicron Di Indonesia Menggunakan Metode Naïve Bayes
[Analysis Of News Sentiment And Public Opinion On Omicron Virus In Indonesia Using The Naïve Bayes Method] The Covid-19 virus continues to mutate to form new variants. The last detected variant, the Omicron variant, is known as the B.1.1.529 variant. This variant was first reported from South Africa on 24 November 2021 and has now spread worldwide. In July 2022 Omicron cases experienced a spike. This has led to a lot of public opinion, especially on social media, about the omicron virus. This study aims to classify public opinion on the emergence of the Omicron virus on Twitter and YouTube social media into positive, negative and neutral classes. The method used in this study is the naïve Bayes algorithm. Naïve Bayes is a method that can be used to classify public opinion sentiment. The results of sentiment analysis research using naïve Bayes produce an accuracy rate of 0.82%. Then the model was tested to read public opinion on Twitter from 5 October 2022 to 27 October 2022. The results for Twitter user sentiment on the keyword Covid 19 were dominated by positive sentiment with a percentage of 85%. And sentiment with the keyword Omicron is still dominated by positive sentiment with a percentage of 49%. It was stated that the results of the classification on data for October 2022 meant that people were much more optimistic about the disappearance of the Omicron virus. Henceforth this research can be improved by adding data or using a different algorithm or implementing an existing algorithm