Imamah, Lina Haritsatul (2021) ANALISIS SENTIMEN MENGGUNAKAN ALGORITMA NAIVE BAYES UNTUK MELIHAT PRESEPSI MASYARAKAT TERHADAP PANDEMI COVID19 PADA MEDIA SOSIAL TWITTER. Undergraduate thesis, Universitas Stikubank.
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Abstract
Pada tanggal 1 Desember tahun 2019 pertama kalinya peristiwa menyebarnya virus corona yang terdeteksi di kota Wuhan Tiongkok. Hingga tanggal 14 November 2020 dilaporkan lebih dari 219 negara termasuk negara Indonesia. Negara Indonesia termasuk negara dengan jumlah korban jiwa banyak akibat pandemi sehingga penduduk Indonesia mengalami keadaan yang tidak biasanya. Kondisi ini menyebabkan bayak Pegawai yang diberhentikan kerja secara hormat, semakin banyak pengangguran dan banyak masyarakat mengeluh karena keadaan ekonominya yang menurun drastis. Di zaman seperti ini banyak masyarakat yang mengapresiasikan opininya pada media sosial twitter. pada penelitian ini data di ambil cuitan tweets dari twitter dengan kata kunci #vaksin dan #corona untuk diolah dan diklasifikasikan teks dengan menggunakan metode analisis sentimen. Proses klasifikasi dibagi menjadi dua kelas yaitu kelas sentiment negatif dan kelas sentiment positif. Data yang diproses berjumlah 500 tweets terdiri dari 350 data training dan 150 data testing. Pada studi kasus ini peneliti dapat menunjukan klasifikasi dengan hasil akurasi yang didapat sebesar 84%. Precision kelas negatif sebesar 88% dan precision kelas positif sebesar 82% dan 85%Netral. On December 1, 2019 the first time the corona virus spread was detected in the Chinese city of Wuhan. As of November 14, 2020, more than 219 countries including Indonesia have been reported. Indonesia is one of the countries with a large number of fatalities due to the pandemic so that the population of Indonesia is experiencing unusual circumstances. This condition causes employees who are dismissed from work respectfully, more and more unemployed and many people complain because of the viii deteriorating economic situation. In this era, many people appreciate his opinion on social media twitter. in this study the data was taken tweets from twitter with keywords #vaksin and #corona to process and classify text using sentiment analysis methods. The classification process is divided into two classes, namely negative sentiment class and positive sentiment class. The data processed amounted to 500 tweets consisting of 350 training data and 150 data testing. In this case study, researchers were able to show classification with accuracy results obtained by 84%. Precision negative class by 88% and precision positive class by 82% and 85% Neutral.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | SKR.I.05.01.2035 NIM 17.01.53.0075 |
| Uncontrolled Keywords: | Naïve Bayes Classifier, Analisa Sentimen, Klasifikasi, Twitter, Pandemi Covid19,Python Naïve Bayes Classifier, Sentiment Analysis, Classification, Twitter, Covid19 Pandemic,Python. |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software |
| Faculty / Institution: | Fakultas Teknologi Informasi > Program Studi Teknik Informatika |
| Depositing User: | Teteh Hayati |
| Date Deposited: | 10 Nov 2021 06:27 |
| Last Modified: | 10 Nov 2021 06:27 |
| URI: | https://eprints.unisbank.ac.id/id/eprint/8035 |
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