F. Aryanto, Ahmad Fauzi, Anis Fitri Nur Masruriyah, April Lia Hananto, Darmansyah
{"title":"Sentiment Analysis Of Vaccination Using The K-Nearest Neighbor Algorithm","authors":"F. Aryanto, Ahmad Fauzi, Anis Fitri Nur Masruriyah, April Lia Hananto, Darmansyah","doi":"10.59805/ecsit.v1i1.6","DOIUrl":null,"url":null,"abstract":"The outbreak of the COVID-19 virus that attacked the country of Indonesia made the government implement a policy, namely giving vaccinations. Since the announcement of the government's policy on administering the COVID-19 vaccine in January 2021, there have been a lot of discussions, especially on social media. One of the social media that is widely used by the public for opinions is Twitter. this has resulted in Twitter becoming a medium for expressing people's thoughts on administering the COVID-19 vaccine. Opinions generated can be positive, negative, or neutral towards vaccine administration. Based on the description of the problem, the study aims to analyze the sentiments of netizens regarding government policies in administering vaccinations. The method used is the KNN Algorithm to carry out sentiment analysis through public opinion on Twitter social media. The results sentiment with the highest value is positive which has more than 150 sentences. Then it produces an accuracy of 86.6% Precision of 85% and Recalls of 81%.","PeriodicalId":202727,"journal":{"name":"Edutran Computer Science and Information Technology","volume":"141 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Edutran Computer Science and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.59805/ecsit.v1i1.6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The outbreak of the COVID-19 virus that attacked the country of Indonesia made the government implement a policy, namely giving vaccinations. Since the announcement of the government's policy on administering the COVID-19 vaccine in January 2021, there have been a lot of discussions, especially on social media. One of the social media that is widely used by the public for opinions is Twitter. this has resulted in Twitter becoming a medium for expressing people's thoughts on administering the COVID-19 vaccine. Opinions generated can be positive, negative, or neutral towards vaccine administration. Based on the description of the problem, the study aims to analyze the sentiments of netizens regarding government policies in administering vaccinations. The method used is the KNN Algorithm to carry out sentiment analysis through public opinion on Twitter social media. The results sentiment with the highest value is positive which has more than 150 sentences. Then it produces an accuracy of 86.6% Precision of 85% and Recalls of 81%.