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Linear Regression Method Predicting BMRI Stock Price Using Machine Learning

Kholik Zaenudin Ashar(1*),Muhammad Raffi Muttaqin(2),Yudhi Raymond Ramadhan(3)
(1) Sekolah Tinggi Teknologi Wastukancana
(2) Sekolah Tinggi Teknologi Wastukancana
(3) Sekolah Tinggi Teknologi Wastukancana
(*) Corresponding Author
DOI : 10.35889/jutisi.v12i3.1427

Abstract

Investing in stocks carries considerable risk as stock prices fluctuate depending on market conditions and company performance. Therefore, it is necessary to analyze stock price movements so that investors can use the analysis results to make investment decisions. In this study, using the linear regression method, machine learning is used to predict the closing price of Bank Mandiri Tbk (BMRI) shares. The attributes used in this research are Open, High, and Low as inputs and Close labels to determine the prediction value. The data obtained is processed using Visual Studio Code tools with the Python programming language. This research focuses on assessing the value of error and precision, mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), and mean absolute percentage error (MAPE). Based on the tests conducted, the results obtained an error value of 960.97 for the MSE value, 30.9995 for the RMSE value, and 0.57% for the MAPE value.

 

Keywords


BMRI; Linear Regression; Stock Price Prediction

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