Comparative Analysis of Bitcoin Price Movement Prediction using ARIMA and FBProphet

Abstract

The rise of Bitcoin and other cryptocurrencies has transformed the financial landscape, especially emerging markets in Indonesia, where adoption rates have grown significantly in recent years. With Indonesia ranked among the top countries in terms of global crypto usage, the demand for innovative strategies to predict Bitcoin price movements has increased. This study compares the ARIMA and Facebook Prophet models for forecasting Bitcoin price trends using historical data from Indodax, one of Indonesia's largest cryptocurrency exchanges, covering the period from 2019 to 2024. Pre-processing involved handling missing data and applying feature engineering techniques such as moving averages and rolling statistics. Results indicate that ARIMA outperformed FBProphet in accuracy, achieving an RMSE of$\mathbf{2 6, 8 9 6, 5 5 8}$and MAPE of$\mathbf{1. 8 1 \%}$. While FBProphet excelled in capturing seasonal patterns despite its higher RMSE and MAPE, ARIMA demonstrated superior precision but struggled with high market volatility. This study highlights the complementary strengths of both models and provides insights to enhance cryptocurrency price prediction in dynamic markets such as Indonesia.