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FORECASTING SAHAM MENGGUNAKAN METODE CONVULATION NEURAL NETWORKS (CNN) – LONG SHORT-TERM MEMORY (LSTM)

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Stock is one of the financial instruments of the stock market that is in great demand by the public. Stock prices can change over time. There are several factors that cause changes in stock prices. Based on this, a system can predict stock price data using the Convolutional Neural Network (CNN) - Long Short-Term Memory (LSTM) method. The data used in this prediction is data for the last 2 years from Facebook and Tesla stocks. The amount of data used is 505 data, then divided into 75% training data and 25% test data. In conducting the test, each data is tested with different configuration combinations. The results of the test show that the configuration that most influences the loss results from predictions is the epoch and the amount of data used. Facebook shares with epoch 200 configuration and padding off have smaller loss values, namely RMSE: 6.72 and MAE: 5.12.

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Inventory Code Barcode Call Number Location Status
2307000534T82695T826952023Central Library (Referens)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T826952023
Publisher
Inderalaya : Jurusan Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya.,
Collation
xiii, 80 hlm.; ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
006.754 07
Content Type
-
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Jurusan Teknik Informatika
Situs Jejaring Sosial
Specific Detail Info
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Statement of Responsibility
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