BBRI Stock Trend and Volatility Analysis Using Moving Average and Standard Deviation

Main Article Content

Andreas Doloksaribu

Abstract

Bank Rakyat Indonesia (BBRI) is one of the largest banks in Indonesia with significant market capitalization. This study aims to analyze price trend movements and stock volatility of BBRI for the period of January 2023 - October 2025 using Simple Moving Average (SMA) 20 and 50 days and Standard Deviation 20 days. Daily data (672 observations) were analyzed to identify trend patterns and investment risk levels. The results show that BBRI stock experienced a strong uptrend phase in 2023 (+33.1%), followed by a rally to a peak of IDR 5,763 in May 2024. However, the mid-2024 period was marked by high volatility with a whipsaw pattern (false signals), where the October 2024 Death Cross confirmed a final decline to the lowest level of IDR 3,176 (-44.9% from the peak). Volatility varied from 40 IDR (lowest, July-August 2023) to 425 IDR (highest, May-June 2024), indicating a negative correlation with trend strength. Moving Average is effective in identifying major trend changes, providing practical implications for technical analysis-based investment strategies.

Article Details

How to Cite
Doloksaribu, A. (2025). BBRI Stock Trend and Volatility Analysis Using Moving Average and Standard Deviation. JITSI : Jurnal Ilmiah Teknologi Sistem Informasi, 6(4), 389 - 394. https://doi.org/10.62527/jitsi.6.4.514
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References

[1] M. Hilman and A. Mulyana, "Komparasi Algoritma Moving Average dan Exponential Smoothing dalam Prediksi Harga Saham Menggunakan Python," JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer), vol. 8, no. 1, pp. 15-24, 2022.
[2] H. Susanto and S. Sudadi, "Implementasi Algoritma Simple Moving Average Untuk Memprediksi Penjualan," Jurnal Teknologi Informasi dan Komunikasi, vol. 11, no. 2, pp. 18-25, 2020.
[3] A. Pratama and M. Syafruddin, "Analisis Perbandingan Akurasi Metode Simple Moving Average dan Exponential Moving Average dalam Memprediksi Harga Saham Perbankan," Jurnal Akuntansi dan Keuangan Daerah, vol. 17, no. 2, pp. 45-56, 2022.
[4] W. P. Sari and R. Hidayat, "Analisis Volatilitas Return Saham Perbankan di Bursa Efek Indonesia Pasca Pandemi Covid-19," Jurnal Ekonomi dan Bisnis Dharma Andalas, vol. 25, no. 1, pp. 112-125, 2023.
[5] Z. Bodie, A. Kane, and A. J. Marcus, Investments, 10th ed. New York: McGraw-Hill Education, 2014.
[6] J. J. Murphy, Technical Analysis of the Financial Markets. New York: New York Institute of Finance, 1999.
[7] S. B. Achelis, Technical Analysis from A to Z, 2nd ed. New York: McGraw-Hill, 2001.
[8] E. Tandelilin, Portofolio dan Investasi: Teori dan Aplikasi. Yogyakarta: Kanisius, 2010.
[9] D. Kurniawan and A. Saputra, "Penerapan Metode Moving Average pada Sistem Peramalan Persediaan Barang Berbasis Web," Jurnal Media Informatika Budidarma, vol. 5, no. 1, pp. 23-30, 2021.
[10] R. Wijaya, "Penerapan Analisis Teknikal Menggunakan Indikator Moving Average pada Saham PT Bank Rakyat Indonesia (Persero) Tbk," Jurnal Ilmiah Mahasiswa FEB, vol. 9, no. 2, 2021.
[11] B. Santoso, "Analisis Prediksi Harga Saham Menggunakan Moving Average: Studi Kasus BCA," Jurnal Ekonomi dan Bisnis, vol. 9, no. 1, pp. 78-92, 2021.
[12] R. Pratama and D. Kusuma, "Efektivitas Moving Average pada Saham Sektor Finansial di Bursa Efek Indonesia," Jurnal Manajemen dan Keuangan, vol. 12, no. 2, pp. 145-158, 2023.
[13] Bursa Efek Indonesia, "Data Historis Saham BBRI," 2025. [Online]. Available: https://www.idx.co.id.