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All Journal Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Nur, Fahad Abdul
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Computer Science & IT Control & Systems Engineering

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Analisa Sentimen Twitter Vaksin Covid-19 di Indonesia dengan Metode Support Vector Machine Sulastri, S; Nur, Fahad Abdul
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 3 (2024): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i3.443

Abstract

In today's digital era, Twitter is very widely used by the public as a means of communication. These facilities provide freedom in expressing opinions and / or opinions on twitter social media. Opinions in social media twitter can be called tweets. Opinions that often arise are very diverse in expression and meaning in the context of the problem being discussed. Tweets analyzed in this study are related to the issue of the Coronavirus in Indonesia. The data used in this study, 500 tweet data with 350 training data and 150 test data. The tools used in the classification process is the Python programming language. Then for the method used in the classification is the vector support machine method with the sentiment data used, namely positive and negative. The results are given in the support vector machine method in a value of 66%, with a recall of 61% and a precision of 74%. Therefore, the support vector machine method is quite good in classifying.
Co-Authors Sulastri, S