Publisher

UIMUIM

Journal UIM | Zeta - Math JournalUIM | Zeta - Math Journal Abstract

The Covid-19 pandemic that has occurred for approximately two years since 2020 in Indonesia has had a tremendous impact on the domestic economy. The impact is felt by many sectors, including the banking sector. In the banking sector, the economic downturn is also felt by investors, especially stock investors. Due to fluctuating stock price conditions, it also increases the number of uncertainties. This needs to be taken seriously by business people in the banking sector and investors so that companies are still able to operate in the midst of post-pandemic conditions. In times of crisis like today, investors, especially stock investors, have begun to adapt to the development of stock prices by taking an approach using advances in information technology. Updates from the field of information technology such as the use of machine learning with a technical approach or forecasting method have now begun to be utilized. This study aims to Analyze and forecast the closing price of shares of PT Bank Rakyat Indonesia Tbk using the Multiple Linear Regression method using reference stock data before and after covid-19 with a time span between 2018 and 2022. The forecasting results produced an RMSE value of 0.0256 in the condition of 90% training data and 10% test data.

Conclusion

From the overall simulation results, it can be concluded that the Multiple Linear Regression method has good performance seen from its low error value with the best Root Mean Squared Error (RMSE) value occurring in the last simulation with a value of 0.The resulting Root Mean Squared Error (RMSE) value has met the objectives of the simulations carried out in this study.This method can be used as an alternative to simple forecasting methods because of its ease of application and it is possible that in the future this Multiple Linear Regression method can be used to forecast more complex data and compared with several other forecasting methods to test its accuracy.

Future Research

Berdasarkan penelitian ini, terdapat beberapa saran penelitian lanjutan yang dapat dikembangkan. Pertama, penelitian selanjutnya dapat mengeksplorasi penggunaan algoritma machine learning yang lebih kompleks, seperti Recurrent Neural Networks (RNN) atau Long Short-Term Memory (LSTM), untuk meningkatkan akurasi prediksi harga saham. Kedua, penelitian dapat memperluas cakupan variabel independen yang digunakan dalam model regresi, termasuk faktor-faktor makroekonomi dan sentimen pasar, untuk memberikan gambaran yang lebih komprehensif tentang faktor-faktor yang memengaruhi harga saham. Ketiga, penelitian dapat dilakukan untuk membandingkan kinerja model regresi dengan metode investasi yang berbeda, seperti strategi buy-and-hold atau strategi aktif, untuk mengevaluasi potensi keuntungan dan risiko dari penggunaan model tersebut dalam pengambilan keputusan investasi.

References

1. Peramalan Harga Saham Perusahaan Perbankan dengan Market Capitalization Terbesar di Indonesia Pasca-Covid19... doi.org/10.31605/jomta.v5i2.3238Peramalan Harga Saham Perusahaan Perbankan dengan Market Capitalization Terbesar di Indonesia Pasca Covid19 doi 10 31605 jomta v5i2 3238
2. Stock Price dan COVID-19 : Sebuah Studi Perbandingan pada Sektor Perbankan Indonesia | Jurnal Akuntansi,... jurnal.polibatam.ac.id/index.php/JAEMB/article/view/3149Stock Price dan COVID 19 Sebuah Studi Perbandingan pada Sektor Perbankan Indonesia Jurnal Akuntansi jurnal polibatam ac index php JAEMB article view 3149

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