Prediksi Harga Saham Bank Bri Menggunakan Algoritma Simple Linear Regression Sebagai Strategi Jual Beli Saham

Janur, Syahputra (2021) Prediksi Harga Saham Bank Bri Menggunakan Algoritma Simple Linear Regression Sebagai Strategi Jual Beli Saham. Undergraduate Thesis thesis, Institut Teknologi Telkom Purwokerto.

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Abstract

Stocks are securities that serve as proof of an investor's ownership in a company; however, the fluctuating nature of stock prices makes stock prices difficult to predict. Stock prediction is an attempt to forecast the stock price, particularly in the Bank Rakyat Indonesia company, in order to increase investors' profit opportunities when making investment decisions. The analysis and selection strategy is determined by the nature of the investor, the nature of the first investor is a passive investor who prefers to avoid big losses, the goal is to be free from having to make decisions repeatedly. The second nature of investors is aggressive investors who are willing to devote time and attention to choosing 4 good and more promising securities. During the COVID-19 pandemic, Bank BRI's shares rose and fell significantly in four months, demonstrating the stock's sensitivity to an event. The prediction itself necessitates the use of time series data. Simple Linear Regression is used for time series data because it can handle time series data. Based on these problems, the Bank Rakyat Indonesia company will conduct stock prediction research using the Simple Linear Regression method. The Bank Rakyat Indonesia stock price data was obtained from the investing.com website from January 1, 2008 to June 1, 2020. The data is processed in stages, beginning with preprocessing and progressing to dividing the dataset into training and testing data. The attributes used in this study are Date and Price, and the data distribution is 80:20, resulting in train and test accuracy of 0.89 and 0.91, respectively, which are then entered into the simple linear regression model for prediction. The prediction error rates were calculated using MAPE and MSE, yielding 13.751 percent and 122114.84 for training data, 13.773 percent and 115103.12 for test data, and 13.755 percent and 120710.65 for comprehensive data. Based on these results, the MAPE test is superior in calculating the prediction error in the simple linear regression model for predicting the stock price of BRI Bank. The Simple Linear Regression method can be used to predict stocks in BRI Bank. Keywords: stokcs, Simple linear regression, MAPE, MSE

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