Sentiment Analisis Terhadap Cryptocurrency Berdasarkan Comment Dan Reply Pada Platform Twitter
DOI:
https://doi.org/10.33557/journalisi.v3i2.124Keywords:
analisis sentiment, klasifikasi, opini , cryptocurrency, metode, naive bayes, support vector machine, accuracyAbstract
Analisis sentiment saat ini banyak di gunakan masyarat sebagai bahan untuk mengetahui pendapat atau opini masyarakat
tentang berbagai macam hal. Dengan menggunakan sentiment analisis kita dapat mengklasifikasikan data apakah data tersebut
termasuk opini netral opini positif opini negatif. Penelitian ini membahas tentang analisis sentiment untuk mengukur tingkat
akurasi dari pendapat masyarakat pada tiga cryptocurrency yaitu Bitcoin,ethereum,ripple dengan metode Naive Bayes dan
support vector machine yang berguna untuk mengetahui nilai akurasi yang tertinggi dari dua metode yang digunakan dalam
penelitian ini. Ada banyak metode yang bisa digunakan untuk mengkasifikasikan opini tersebut, namun penelitian ini dipilih
metode Naive Bayes dan Support vector machine, dengan alasan metede tersebut banyak di gunakan oleh peneliti lain dan
menghasilkan nilai akurasi yang tinggi. Hasil dari penelitian ini adalah berupa data perbandingan dari akurasi. hasil akurasi
dari 3 cryptocurrency SVM lebih besar dari pada nilai akurasi 3 cryptocurrency Naive Bayes.
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