PREDIKSI PERGERAKAN HARGA SAHAM PADA SEKTOR FARMASI MENGGUNAKAN ALGORITMA LONG SHORT-TERM MEMORY
Nowadays, there are many investment options available to the public, one of which is investing in stocks. Stocks investment can make an investor get big profits, but also a big risk of loss. Stocks are valuable documents to represents the ownership of a company. Stock prices are volatile due to vari...
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2021-07-23.
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| 260 | |c 2021-07-23. | ||
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| 500 | |a http://repository.upnvj.ac.id/11274/2/ARTIKEL%20KI.pdf | ||
| 520 | |a Nowadays, there are many investment options available to the public, one of which is investing in stocks. Stocks investment can make an investor get big profits, but also a big risk of loss. Stocks are valuable documents to represents the ownership of a company. Stock prices are volatile due to various internal and external factors of the company. In the midst of the Covid-19 pandemic, it greatly affected the stock price of each company, one of which was a pharmaceutical company. Pharmaceutical companies are expected to experience a decrease in shares due to the pandemic, but can also get a share price increase due to the increasing number of drug sales and research for the public. With this erratic change in stock prices, a system is needed to predict stock price movements. This study uses the Long Short-Term Memory algorithm to predict stock prices, where Kalbe Farma is selected as a pharmaceutical company. Data is obtained from the site yahoo finance. The next process is to process the data by testing the model formed using the hidden layer, units and epoch and batch size variations which produce stock price predictions with an average value of RMSE 27.310. | ||
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