Santoso, Andy and Hansun, Seng (2019) Prediksi IHSG dengan Backpropagation Neural Network. Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 3 (2). ISSN 2580-0760
Full text not available from this repository.Abstract
IDX Composite is a combination of all common stock and preferred stock which registered on Bursa Efek Indonesia (BEI). IDX Composite is often used by investor to predict the stock price to get profit. But, to predict the stock price is not easy, hence it yields a high risk to investor. This study offers the usage of backpropagation algorithm to minimize the risk. Backpropagation is a supervised algorithm and will be made in Python programming language, in this case, backpropagation will use and learn the past 5 days data to predict the outcome. Also, this study shows that backpropagation have a high accuracy which reflects in Mean Square Error Testing value of 320.49865083640924 to predict IDX Composite using 0.3 learning rate and 3000 epoch.
| Item Type: | Article |
|---|---|
| Subjects: | 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 005 Computer Programming 300 Social Sciences > 330 Economics > 332 Financial Economics (Shares, Investment) |
| Divisions: | Faculty of Engineering & Informatics > Informatics |
| Depositing User: | Administrator UMN Library |
| Date Deposited: | 21 Oct 2021 03:10 |
| Last Modified: | 21 Oct 2021 03:10 |
| URI: | https://kc.umn.ac.id/id/eprint/18930 |
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