Prediksi Harga Saham Syariah dengan Triple Exponential Smoothing Multiplicative
DOI:
https://doi.org/10.21580/square.2024.6.2.23602Keywords:
predictions, sharia shares, triple exponential smoothingAbstract
The prediction of sharia stock prices is currently an important concern for investors who want to invest according to Islamic principles. Investors generally invest to achieve profits, which are measured by the magnitude of returns or the rate of return on those sharia-compliant stocks. However, there is also a risk of loss if the investor makes the wrong decision. Often, investors simply guess whether the stock price will go up or down. In sharia stock analysis, accurate forecasting techniques are needed to help investors minimize risk and maximize potential returns. This research aims to predict the stock price of Bank Syariah Indonesia (BRIS. JK), which is one of the sharia stocks highly sought after by stock investors. The prediction for the next year is conducted using the multiplicative triple exponential smoothing method as a guide for investors in decision-making. This method was chosen because of its ability to capture seasonal patterns and trends based on historical stock data. The forecasting results show that the price of BRIS.JK shares will continue to rise over the next year. This provides valuable information for investors to consider investing in that stock.
Keywords: predictions, sharia shares, triple exponential smoothing.
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References
Amiroch, S. (2015). Prediksi Harga Saham menggunakan Jaringan Syaraf Tiruan Backpropagation. Unisda Journal Mathematics and Computer Science, 1(1), 75–84.
Anggraeni, A. S., Utama, R. C., & Wati, D. C. (2022). Penghalusan eksponensial dan dekomposisi saham apple.inc. Jurnal Sintak, 1(1), 24–30.
Chandrasa, M. A. D., Lesmana, E., & Hertini, E. (2020). Peramalan Jumlah Kedatangan Wisatawan Mancanegara Ke Indonesia Dengan Metode Holt-Winters Dan Hubungannya Terhadap Pendapatan Devisa Pariwisata. Teorema: Teori Dan Riset Matematika, 5(2), 230.
Kalekar, P. (2004). Time series forecasting using Holt-Winters exponential smoothing. Kanwal Rekhi School of Information Technology, 04329008, 1–13.
Makridakis, S. D. (1999). Metode dan Aplikasi Peramalan. Terjemahan Untung Sus Andriyanto dan Abdul basith. Erlangga .
Pangruruk, F. A., Barus, S. P., & Siregar, B. (2021). Peramalan Harga Saham Tutup Dengan Metode Interpolasi Polinom Lagrange. Seminar Nasional Variansi …, Snso, 118–126.
Purnama, D. I., & Hendarsin, O. P. (2020). Peramalan Jumlah Penumpang Berangkat Melalui Transportasi Udara di Sulawesi Tengah Menggunakan Support Vector Regression (SVR). Jambura Journal of Mathematics, 2(2), 49–59.
Rosadi, D. (2012). Ekonometrika Dan Analisis Runtun Waktu Terapan. CV. Andi Offset.
Sofiyati, Noor; Hayati, Afifah; Muhassanah, N. (2024). Winters Exponential Smoothing untuk Peramalan Harga Saham PT Astra International Tbk. Jurnal Ilmiah Matematika Dan Pendidikan Matematika, 15(2), 129–138.
Sungkawa, I., & Megasari, R. T. (2011). Penerapan Ukuran Ketepatan Nilai Ramalan Data Deret Waktu dalam Seleksi Model Peramalan Volume Penjualan PT Satriamandiri Citramulia. ComTech: Computer, Mathematics and Engineering Applications, 2(2), 636.
Trimulya, A., Sfaifurrahman, & Setyaningsih, F. A. (2015). Implementasi jaringan syaraf tiruan metode backpropagation untuk memprediksi harga saham 1,3. Coding, 03(2), 66–75.
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