IMPLEMENTASI NAÏVE BAYES CLASSIFIER PADA TWITTER DALAM ANALISIS SENTIMEN TERHADAP VARIAN BARU CORONA VIRUS OMICRON

Simple item page
dc.contributor.authorEsmeralda, Irtha Bella
dc.contributor.supervisorElfizar, Elfizar
dc.date.accessioned2023-08-10T03:39:01Z
dc.date.available2023-08-10T03:39:01Z
dc.date.issued2023-06
dc.description.abstractOmicron is a new variant of the Corona virus that was first reported to the World Health Organization (WHO) from South Africa on November 24, 2021. The amount of information related to the Omicron virus that is spread in the form of text on the internet and on social media sites like Twitter is of interest to researchers. This study aims to determine public sentiment from Twitter users about the omicron virus, then determine sentiment classification using the Nave Bayes Classifier and calculate the level of accuracy of the method in sentiment analysis. The data used is 1350 data points using two data testing scenarios, namely the first scenario, Split Validation, using a data ratio of 70%:30%, 80%:20%, and 90%:10%. The second scenario uses cross-validation, divided into 10 tests. Sentiment classifiers are divided into three classes: neutral, fearful, and fearless. The classification process is carried out by means of data pre-processing and weighting using the TF-IDF technique. The final results of the classification process get the highest accuracy values of 85%, 81% precision, and 86% recall in the split validation test with a 90:10 data division. Testing data with cross-validation resulted in the highest accuracy of 93,1% accuracy, 36,6% precision, and 98% recall, with a fold value of 1.en_US
dc.description.sponsorshipFakultas Matematika dan Ilmu Pengetahuan Alamen_US
dc.identifier.citationPerpustakaanen_US
dc.identifier.otherElfitra
dc.identifier.urihttps://repository.unri.ac.id/handle/123456789/11115
dc.language.isoenen_US
dc.publisherElfitraen_US
dc.subjectSentiment Analysisen_US
dc.subjectCross Validationen_US
dc.subjectFolden_US
dc.subjectSplit Validationen_US
dc.subjectNaïve Bayes Classifieren_US
dc.subjectOmicronen_US
dc.subjectTF-IDFen_US
dc.subjectData Testingen_US
dc.subjectTwitteren_US
dc.subjectVirusen_US
dc.titleIMPLEMENTASI NAÏVE BAYES CLASSIFIER PADA TWITTER DALAM ANALISIS SENTIMEN TERHADAP VARIAN BARU CORONA VIRUS OMICRONen_US
dc.typeArticleen_US

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Irtha Bella Esmeralda - Copy_compressed.pdf
Size:
231.25 KB
Format:
Unknown data format
Description:
artikel
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Sistem Infomasi