Prediksi Pergerakan Saham BBRI ditengah Issue Ancaman Resesi 2023 dengan Pendekatan Machine Learning

Wahyu Cahyo Utomo
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引用次数: 0

Abstract

The economic recovery after the Covid-19 pandemic is becoming increasingly challenging. According to several experts, a global recession is expected to occur in 2023, necessitating contributions from various fields of knowledge to address this situation. Machine learning is one method that can contribute by forecasting stock price movements. This research attempts to address the issues faced by traders in observing the potential movement of BBRI stock under the recession issue in 2023. Furthermore, this study uses linear regression and Bayesian regression methods to find the best model. By using six-month stock data of BBRI, with attributes such as open, high, low, and close as prediction targets, it is found that the model built using linear regression outperforms Bayesian regression. Based on the testing results, the linear regression model achieved a Dstat of 80% and an RMSE of 595.30, while the Bayesian regression model obtained a Dstat of 80% but a higher RMSE of 660.58. Based on the modeling results in this study, it is concluded that in the first semester of 2023, BBRI stock is still moving upward and is not affected by the recession issue in 2023.
用机器学习方法预测2023年问题威胁缓解期间美国数量的变化
新冠肺炎大流行后的经济复苏正变得越来越具有挑战性。据几位专家称,预计2023年将出现全球经济衰退,需要各个知识领域做出贡献来应对这种情况。机器学习是一种可以预测股价走势的方法。这项研究试图解决交易员在2023年经济衰退问题下观察BBRI股票潜在走势时面临的问题。此外,本研究使用线性回归和贝叶斯回归方法来寻找最佳模型。通过使用BBRI六个月的股票数据,以开盘、高、低、收盘等属性作为预测目标,发现使用线性回归建立的模型优于贝叶斯回归。基于测试结果,线性回归模型获得了80%的Dstat和595.30的均方根误差,而贝叶斯回归模型获得80%的Dsstat和660.58的较高均方根误差。基于本研究的建模结果,得出的结论是,2023年上半年,BBRI股票仍在上涨,不受2023年经济衰退问题的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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