Prediksi Harga Bitcoin Menggunakan Algoritma Random Forest Regressor
Keywords:
Bitcoin, Prediksi Harga, Random ForestAbstract
Bitcoin merupakan salah satu aset kripto dengan tingkat volatilitas harga yang tinggi sehingga diperlukan metode prediksi yang mampu menangkap pola pergerakan harga secara akurat. Penelitian ini bertujuan untuk memprediksi harga penutupan Bitcoin menggunakan algoritma Random Forest Regressor berdasarkan data historis periode 2018–2025. Dataset diperoleh dari Investing.com dan mencakup variabel Open, High, Low, Close, dan Volume. Metodologi penelitian meliputi pengumpulan data, pra-pemrosesan, pembentukan fitur time-series dengan pendekatan lag-1, pembagian data menggunakan time-series split, pelatihan model Random Forest, serta evaluasi kinerja model. Hasil penelitian menunjukkan bahwa Random Forest mampu memodelkan pola pergerakan harga Bitcoin yang bersifat non-linear dan fluktuatif. Prediksi harga Bitcoin periode 2025–2030 dihitung menggunakan pendekatan recursive forecasting dan diinterpretasikan dalam bentuk agregasi tahunan. Hasil prediksi menunjukkan adanya tren kenaikan harga Bitcoin dalam jangka menengah hingga panjang. Penelitian ini diharapkan dapat menjadi referensi dalam pengembangan model prediksi harga aset kripto berbasis machine learning
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