Analisis perbandingan sentimen Corona Virus Disease-2019 (Covid19) pada Twitter Menggunakan Metode Logistic Regression Dan Support Vector Machine (SVM)
DOI:
https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v5i2.2365Keywords:
Sentimen, NLP, Logistic Regression, Support Vector Machine (SVM)Abstract
Melihat perkembangan twitter tersebut maka twitter menjadi salah satu media yang dapat digunakan untuk melakukan analisis sentimen terhadap bebagai topik. Penelitian ini melakukan suatu analisis sentimen terhadap bahasan yang saat ini sering menjadi trending topic di twitter yaitu “CoronaVirus Disease-2019 (covid19)”. Penyebaran virus ini juga langsung dibicarakan oleh banyak kalangan masyarakat twitter, saat ini virus corona tengah menjadi perhatian dunia internasional. Banyaknya jumlah angka korban dan cepatnya penularan virus membuat masyarakat khawatir dan muncul berbagai opini tentang virus corona, Opini inilah yang kemudian di analisa untuk diketahui polaritasnya dengan analisis sentimen. Metode yang digunakan adalah Logistic Regression dan Support Vector Machine (SVM) dimana SVM memiliki nilai akurasi 91,15% dalam data test sedangkan metode Logistic Regression mendapatkan nilai akurasi sebanyak 87,68% dalam data test.
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Copyright (c) 2022 Kelvin Kelvin, Jepri Banjarnahor, Evta Indra -, Marlince NK Nababan, Stiven Hamonangan Sinurat
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