ANALISIS SENTIMEN TWITTER TERHADAP PEPERANGAN RUSIA DAN UKRAINA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE

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dc.contributor.authorAndraini, Fitri
dc.contributor.supervisorMahdiyah, Evfi
dc.date.accessioned2022-11-14T06:47:57Z
dc.date.available2022-11-14T06:47:57Z
dc.date.issued2022-07
dc.description.abstractSentiment analysis is one of the sciences in Text Mining which is used to classify text documents in the form of public opinion. The text document used in this study comes from Twitter using three positive, negative, and neutral labels. The method used was the Support Vector Machine. This study used 2000 data using two data test scenarios, namely, Split Validation and Cross Validation. Testing data with Split Validation was divided into 4 variations, namely, 50%:50%, 70%:30%, 80%:20%, and 90%:10%, while testing data with Cross Validation was divided into 10 tests. The highest accuracy result used the Split Validation test laid in a comparison of 90%: 10%, which is 83.5%, while data testing with Cross Validation had the highest accuracy at K-Fold 7 of 86.0%.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/123456789/10737
dc.language.isoenen_US
dc.publisherElfitraen_US
dc.subjectText Miningen_US
dc.subjectSupport Vector Machineen_US
dc.subjectSplit Validationen_US
dc.subjectCross Validationen_US
dc.subjectK-folden_US
dc.subjectK-fold Cross Validationen_US
dc.titleANALISIS SENTIMEN TWITTER TERHADAP PEPERANGAN RUSIA DAN UKRAINA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINEen_US
dc.typeArticleen_US

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