Penerapan Artificial Neural Network dengan Metode Backpropagation Dalam Memprediksi Harga Saham (Kasus: PT. Bank BCA, Tbk)

Ihda Innar Ridho(1*), Cerah Fitri Ramadhani(2), Agus Perdana Windarto(3),

(1) Universtias Islam Kalimantan Muhammad Arsyad Al Banjari Banjarmasin, Indonesia
(2) STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
(3) STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
(*) Corresponding Author

Abstract


The Indonesia Stock Exchange (IDX) is a marketplace where individuals and investors can purchase or invest their capital in stocks for potential profits. There are currently 800 listed companies on the IDX, and one of them is PT Bank BCA Tbk, the largest private bank in Indonesia with a capital of Rp 42.93 trillion. Stocks serve as securities that demonstrate an investor's ownership in a company. In order to predict the future stock prices of companies, especially PT Bank BCA, and to increase the chances of profit for investors, an analysis is necessary. The purpose of this study is to create a forecast model using the Artificial Neural Network (ANN) method to predict the stock price of Bank BCA. Historical stock price data from Yahoo Finance (finance.yahoo.com) from 2016 to 2022 was used as the dataset. The goal of this research is to examine the effectiveness of the Backpropagation method in predicting Bank BCA's stock price. This research provides valuable information and considerations for investors when deciding whether to buy, hold, or sell their stocks. The accuracy rate of this research is 91.66666667%, with a testing MSE of 0.0010000650, and a total of 7695 epochs.


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DOI: http://dx.doi.org/10.30645/jurasik.v8i1.612

DOI (PDF): http://dx.doi.org/10.30645/jurasik.v8i1.612.g590

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