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Razif Zulvikar Hatuwe
Muhammadiyah University of Sidoarjo, Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Neuroscience

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The Use of Facebook Prophet in Predicting Stock Price Razif Zulvikar Hatuwe; Yulian Findawati
International Journal on Human-Computing Studies Vol. 8 No. 1 (2026): International Journal of Human Computing Studies (IJHCS)
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v8i1.5769

Abstract

This study examines the effectiveness of the Facebook Prophet model in predicting stock prices. The data consist of daily stock prices obtained from Yahoo Finance from July 30, 2019 to July 30, 2024, totaling 1,214 observations. A quantitative time series approach was applied by testing several Prophet configurations, including the basic model, the addition of external regressors, parameter tuning, and their combination. Model performance was evaluated using Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The best results were achieved by the model combining regressors with optimized parameters, producing an MAE of 36.31 and an RMSE of 52.06. Overall, the model provided reasonably accurate predictions for both short- and long-term periods, although bias increased with longer forecast horizons. These findings suggest that Facebook Prophet can be used as a supporting tool for stock price trend analysis based on historical data.
Co-Authors Yulian Findawati