Penggunaan Sentimen Media Sosial X Untuk Memprediksi Fluktuasi Harga Bitcoin Menggunakan Model Bilstm
Abstrak
Perkembangan teknologi digital mendorong pesatnya pertumbuhan pasar aset kripto khususnya bitcoin yang memiliki fluktuasi harga tinggi. Dalam waktu singkat, harga bitcoin dapat berubah signifikan akibat faktor ekonomi dan sentimen publik. Ketidakpastian kebijakan global, seperti kebijakan tarif impor Amerika Serikat tahun 2025 yang dikeluarkan oleh Presiden Donald J. Trump, memicu gejolak pasar dan mendorong investor beralih ke aset digital. Kebijakan serta opini yang disampaikan oleh tokoh berpengaruh di ruang publik sering kali membentuk persepsi investor dan memengaruhi dinamika harga aset digital. Penelitian ini bertujuan untuk menganalisis pengaruh sentimen media sosial X terhadap fluktuasi harga bitcoin dengan menggunakan pendekatan deep learning Bidirectional Long Short-Term Memory (BiLSTM). Fokus penelitian diarahkan pada twit Donald Trump sebagai representasi opini publik yang berpotensi memengaruhi persepsi pasar. Metode yang digunakan adalah pendekatan kuantitatif noneksperimental dengan analisis berbasis deep learning. Data penelitian berupa puluhan ribu twit Donald Trump dan harga historis bitcoin dari CoinMarketCap. Hasil penelitian menunjukkan bahwa sentimen positif dalam twit Donald Trump model mempelajari harga bitcoin cenderung naik, sedangkan sentimen negatif model menunjukkan penurunan harga. Model BiLSTM memiliki performa prediksi yang baik, diukur dengan metrik Mean Absolute Error. Penelitian ini berkontribusi pada pengembangan literatur ekonomi digital melalui integrasi analisis sentimen dan deep learning. Secara praktis hasil dapat dimanfaatkan oleh investor sebagai sinyal awal (early indicator) dalam memprediksi fluktuasi harga bitcoin. Kata Kunci: Bitcoin, Media Sosial X, Analisis Sentimen, Deep learning, BiLSTM
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