Preprint / Version 1

The Use of Facebook Prophet in Predicting Stock Prices

Penggunaan Facebook Prophet dalam Memprediksi Harga Saham

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DOI:

https://doi.org/10.21070/ups.10304

Keywords:

Facebook Prophet, MAE, RMSE, Time Series, Stock Price Forecasting

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.

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References

Jange, B., Studi, P., Akuntansi, K., & Riau, D. (2021). Prediksi Harga Saham Bank BCA Menggunakan Prophet. In Journal of Trends Economics and Accounting Research (Vol. 2, Issue 1).

Santoso, R. S., Kartika, F., & Dewi, S. (2024). Konfigurasi Model Prophet Untuk Prediksi Harga Saham Sektor Teknologi di Indonesia Yang Akurat. In Jurnal Buana Informatika (Vol. 15, Issue 1).

Puspaning Ramadhan, V., Yulian Pamuji, F., & History, A. (2022). Jurnal Teknologi dan Manajemen Informatika Analisis Perbandingan Algoritma Forecasting dalam Prediksi Harga Saham LQ45 PT Bank Mandiri Sekuritas (BMRI) Article Info ABSTRACT. 8, 39–45. http://http://jurnal.unmer.ac.id/index.php/jtmi

Nuzul Hakim, L., Studi Manajemen, P., Muhammadiyah Kalianda, S., & Ekonomi Dan Bisnis, F. (2022). Analisis Pengaruh Inflasi Dan Kurs Terhadap Fluktuasi Nilai Saham (Studi Kasus Pada Perusahaan Telekomunikasi Yang Terdaftar Di Bursa Efek Indonesia Periode 2019-2021). In Jurnal Riset Akuntansi dan Manajemen (Vol. 11, Issue 4).

Menculini, L., Marini, A., Proietti, M., Garinei, A., Bozza, A., Moretti, C., & Marconi, M. (2021). Comparing Prophet and Deep Learning to ARIMA in Forecasting Wholesale Food Prices. Forecasting, 3(3), 644–662. https://doi.org/10.3390/forecast3030040

Made Wahyuliantini, N. (n.d.). PENGARUH HARGA SAHAM, VOLUME PERDAGANGAN SAHAM, DAN VOLATILITAS RETURN SAHAM PADA BID-ASK SPREAD Anak Agung Gede Suarjaya (2).

Khaira, U., Eko, P., Utomo, P., Suratno, T., & Gulo, C. S. (2019). PREDIKSI INDEKS HARGA SAHAM GABUNGAN (IHSG) MENGGUNAKAN ALGORITMA AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA). In JUSS) Jurnal Sains dan Sistem Informasi (Vol. 2, Issue 2).

Kaninde, S., Mahajan, M., Janghale, A., & Joshi, B. (2022). Stock Price Prediction using Facebook Prophet. ITM Web of Conferences, 44, 03060. https://doi.org/10.1051/itmconf/20224403060

Br Sitepu, F. T., Sirait, V. A., & Yunis, R. (2021). Analisis Runtun Waktu Untuk Memprediksi Jumlah Mahasiswa Baru Dengan Model Prophet Facebook. Paradigma - Jurnal Komputer Dan Informatika, 23(1). https://doi.org/10.31294/p.v23i1.9756

Avicenna, K., Endang, W. ;, Pamungkas, W., Kom, S., & Kom, M. (n.d.). IMPLEMENTASI ALGORITMA LSTM UNTUK PREDIKSI HARGA SAHAM PADA SITUS YAHOO FINANCE DENGAN MENERAPKAN MICROSERVICE.

Huang, Q. (2022). Forecasting Stock Prices Using Multi-Macroeconomic Regressors Based on the Facebook Prophet Model. In BCP Business & Management EMEHSS (Vol. 2022).

Riady, S. R. (2023). Stock Price Prediction using Prophet Facebook Algorithm for BBCA and TLKM. International Journal of Advances in Data and Information Systems, 4(2). https://doi.org/10.25008/ijadis.v4i2.1258

Sai Kopparthi, A., Vrunda Kopparthi, A., Anusha Penumarthi, G., & Kumar Kolluru, P. (2024). EasyChair Preprint Exploring Time-Series Forecasting Model for Accurate Dynamic Stock Price Prediction Using Facebook Prophet Exploring Time-Series Forecasting Model for Accurate Dynamic Stock Price Prediction using Facebook Prophet.

Sudha, B. (2025). International Journal of Sciences and Innovation Engineering An Empirical Comparison of Time Series Forecasting Models: Linear Regression, Prophet, and LSTM for Stock Price Prediction. 2(9). https://doi.org/10.70849/ijsci

Wiejaya, A., & Fenriana, I. (2024). Prediksi Harga Saham Top 10 NASDAQ dengan Time Series Prophet. Bit-Tech, 7(2), 252–262. https://doi.org/10.32877/bt.v7i2.1736

Posted

2026-02-20