Forecasting The Stock Market Movements Of Unilever Companies Jakarta During The Covid-19 Pandemic Using Artificial Neural Network
Abstract
The coronavirus (Covid-19) pandemic that has hit Indonesia since March 2020 and has been spreading for a year has led to twists and turns to stock price movements in the capital market. This study aims to determine the accuracy of predictions and movements in the stock price of UNVR companies. JKT in the face of the Covid 19 pandemic. Daily stock data samples from January 01, 2019 to May 15, 2021 taken from https://finance.yahoo. com/quote/ UNVR.JK p=UNVR.JK sources. The data information in this study includes closure as a class or label. Medium attributes the opening, high, low, and volume of the company's stock as an atribut or predictor. As many as 90% datasets as data training to build models and as much as 10% datasets as data testing. Data analysis is done with Artificial Neural Network algorithm to predict the value of the company's share price. The right stock price prediction will provide knowledge information about the current status and future stock price movements. The results showed that the ANN model obtained from the experiment results was with 95% trainining data and 5% testing data. The ANN model has 5 input notes with one bias note, one hidden layer with 5 notes including one bias and produces one output that is stock closing. The validation result of RMSE value model is 62,741 and SE value is 3936.43. The accuracy of the model with a correlation coefficient value of 0.998 means there is a very strong positive correlation between the actual data and the prediction data.
Keywords: Prediction, Stock Price, Artificial Neural Network
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