Analisis Sentimen Berita terhadap Bitcoin dengan Metode Klasifikasi K-Nearest Neighbor

Hari Susanto; Arief Setyanto; Alva Hendi Muhammad

Authors

Hari Susanto Universitas Amikom Yogyakarta
Arief Setyanto Universitas Amikom Yogyakarta
Alva Hendi Muhammad Universitas Amikom Yogyakarta

Keywords:

analisis sentiment, knn, cryptocurrency, bitcoin

Abstract

Globalisasi telah mempengaruhi berbagai aspek kehidupan, terutama dalam kemajuan teknologi informasi dan cryptocurrency sebagai inovasi dalam teknologi finansial. Cryptocurrency seperti Bitcoin berfungsi sebagai media pertukaran dan penyimpan nilai, meski belum diakui sebagai alat pembayaran sah. Pasar cryptocurrency berkembang pesat, dengan lebih dari 10.000 aset crypto beredar di seluruh dunia. Jumlah pengguna meningkat signifikan dari 18 juta pada 2017 menjadi 516 juta pada 2023. Bitcoin mendominasi dengan pangsa pasar 60,14%, menegaskan posisinya sebagai pionir dan mencerminkan minat tinggi dari investor serta masyarakat. Penelitian ini juga mengkaji pergerakan harga Bitcoin melalui analisis sentimen menggunakan metode klasifikasi k-nearest neighbor (KNN). Hasil penelitian ini memberikan wawasan mendalam mengenai dinamika pasar mata uang kripto. Metode KNN mencapai rata-rata akurasi 74,40%, menunjukkan efektivitas pengklasifikasian menggunakan metode ini.

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