Prediksi Fluktuasi Harga Bitcoin Dengan Menggunakan Random Forest Classifier

Chang Hung, Jacky Filbert Wijaya, Victor Victor, Irpan Adiputra Pardosi, Frans Mikael Sinaga

Abstract


Bitcoin merupakan salah satu cryptocurrency paling berharga di dunia dan diperdagangkan di lebih dari 40 bursa di seluruh dunia dan menerima lebih dari 30 mata uang berbeda dengan 250.000 transaksi per hari. Dalam perdagangannya, Bitcoin menunjukkan fluktuasi pada pasar yang diperdagangkan, dalam hal ini fluktuasinya dapat mencapai 10 kali lebih tinggi daripada fluktuasi nilai tukar mata uang asing. Karena fluktuasi harga bitcoin yang masif dan tinggi, prediksi fluktuasi harga sangat dibutuhkan, terutama karena harga bitcoin bergerak dengan sangat acak. Untuk melalukan prediksi flutuktuasi harga, Random Forest classifier merupakan salah satu algoritma machine learning yang sering digunakan untuk prediksi, kesehatan, artificial intelligence, dll. K-means clustering juga dipergunakan untuk membantu algoritma random forest classifier dalam hal mengkluster data. Hasil dari penelitian ini yaitu melakukan prediksi terhadap naik atau turunnya harga bitcoin dengan akurasi sebanyak 71% yang didapatkan dari perbandingan hasil prediksi dan data asli dengan bantuan algoritma confusion matrix.

Keywords


Bitcoin; K-Means Clustering; Random Forest Classifier; Confusion Matrix

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DOI: https://doi.org/10.55601/jsm.v24i2.1024

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