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Implementasi Long Short-Term Memory Pada Harga Saham Perusahaan Perkebunan Di Indonesia

Unisda Journal of Mathematics and Computer Science (UJMC)

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ISSN 2579-907X
2460-3333
 
Authentication Code dc
 
Title Statement Implementasi Long Short-Term Memory Pada Harga Saham Perusahaan Perkebunan Di Indonesia
 
Added Entry - Uncontrolled Name Yotenka, Rahmadi
El Huda, Fazano Fikri
Prodi Statistika FMIPA Universitas Islam Indonesia
Universitas Islam Indonesia
 
Summary, etc.   The decline and increase in the price of shares of plantation companies is a problem for investors in making decisions to buy or sell shares. Factors influencing the movement of plantation stock prices include CPO commodity price fluctuations, world oil price fluctuations, Rupiah exchange rate fluctuations, government regulations and policies, demands from importing countries, and climate. Forecasting stock prices is expected to help investors to deal with uncertainty in the movement of plantation stock prices. This study applies the Long Short-Term Memory (LSTM) to predict the stock prices of plantation companies using SSMS, LSIP, and SIMP share price data from the period 1 July 2014 - 22 July 2019. Based on the results of the study it was found that the best LSTM model on SSMS shares by using the RMSProp optimizer and 70 hidden neurons produced an RMSE value of 21,328. Then the best LSTM model on LSIP stock by using Adam optimizer and 80 hidden neurons produces an RMSE value of 33,097. Whereas the best LSTM model on SIMP shares using Adamax optimizer and 100 hidden neurons produced an RMSE value of 8,3337.    
 
Publication, Distribution, Etc. Mathematics Department of Mathematics and Natural Sciences Unisda Lamongan
 
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http://e-jurnal.unisda.ac.id/index.php/ujmc/article/view/1927
 
Data Source Entry Unisda Journal of Mathematics and Computer Science (UJMC); Vol 6 No 01 (2020): Unisda Journal of Mathematics and Computer science
 
Language Note eng
 
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