PREDIKSI HARGA SAHAM TWITTER DENGAN LONG SHORT-TERM MEMORY RECURRENT NEURAL NETWORK

  • Ibnu Akil (1*) Universitas Bina Sarana Informatika
  • Indra Chaidir (2)

  • (*) Corresponding Author
Keywords: stock prices prediction, recurrent neural network, long short-term memory

Abstract

Abstract— Today the trading business has become a trend to get money easily without having to work hard as long as you have capital. To get maximum results and avoid losses, it is necessary to have expertise in predicting the ups and downs of the stock market value. The purpose of this research is to utilize machine learning technology to predict the fluctuation of stock value by using the Long Short-Term Memory RNN model. From the results of this study, it was found that LSTM+RNN is suitable for use in single-step models.

Keywords: stock price, machine learning, recurrent neural network, lstm

Abstrak—Dewasa ini bisnis trading menjadi suatu trend untuk mendapatkan uang dengan mudah tanpa harus bekerja keras asalkan memiliki modal. Untuk mendapatkah hasil yang maksimal dan menghindari kerugian maka diperlukan keahlian di dalam memprediksi naik turunya nilai bursa saham. Tujuan dari penelitian ini adalah memanfaatkan teknologi machine learning untuk memprediksi naik turunya nilai saham dengan menggunakan model Long Short-Term Memory RNN. Dari hasil penelitian ini didapatkan bahwa LSTM+RNN cocok untuk digunakan pada model single-step.

Kata kunci: harga saham, machine learning, recurrent neural network, lstm

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Published
2022-08-10
How to Cite
Akil, I., & Chaidir, I. (2022). PREDIKSI HARGA SAHAM TWITTER DENGAN LONG SHORT-TERM MEMORY RECURRENT NEURAL NETWORK. INTI Nusa Mandiri, 17(1), 1 - 7. https://doi.org/10.33480/inti.v17i1.3277
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