Optimisasi Hyperparameter BiLSTM Menggunakan Bayesian Optimization untuk Prediksi Harga Saham
| Dublin Core | PKP Metadata Items | Metadata for this Document | |
| 1. | Title | Title of document | Optimisasi Hyperparameter BiLSTM Menggunakan Bayesian Optimization untuk Prediksi Harga Saham |
| 2. | Creator | Author's name, affiliation, country | Fandi Presly Simamora; Universitas Mikroskil; Indonesia |
| 2. | Creator | Author's name, affiliation, country | Ronsen Purba; Universitas Mikroskil; Indonesia |
| 2. | Creator | Author's name, affiliation, country | Muhammad Fermi Pasha; Universitas Mikroskil; Indonesia |
| 3. | Subject | Discipline(s) | |
| 3. | Subject | Keyword(s) | BiLSTM; Bayesian Optimization; Hyperparameter Tuning; Stock Price Prediction |
| 4. | Description | Abstract | The accuracy of deep learning models in predicting dynamic and non-linear stock market data highly depends on selecting optimal hyperparameters. However, finding optimal hyperparameters can be costly in terms of the model's objective function, as it requires testing all possible combinations of hyperparameter configurations. This research aims to find the optimal hyperparameter configuration for the BiLSTM model using Bayesian Optimization. The study was conducted using three blue-chip stocks from different sectors, namely BBCA, BYAN, and TLKM, with two scenarios of search iterations. The test results show that Bayesian Optimization was able to find the optimal hyperparameter configuration for the BiLSTM model, with the best MAPE values for each stock: BBCA 1.2092%, BYAN 2.0609%, and TLKM 1.2027%. Compared to previous research on Grid Search-BiLSTM, the use of Bayesian Optimization-BiLSTM resulted in lower MAPE values. |
| 5. | Publisher | Organizing agency, location | Department of Mathematics, Universitas Negeri Gorontalo |
| 6. | Contributor | Sponsor(s) | |
| 7. | Date | (YYYY-MM-DD) | 2025-02-01 |
| 8. | Type | Status & genre | Peer-reviewed Article |
| 8. | Type | Type | |
| 9. | Format | File format | |
| 10. | Identifier | Uniform Resource Identifier | https://ejurnal.ung.ac.id/index.php/jjom/article/view/27166 |
| 10. | Identifier | Digital Object Identifier (DOI) | https://doi.org/10.37905/jjom.v7i1.27166 |
| 11. | Source | Title; vol., no. (year) | Jambura Journal of Mathematics; Vol 7, No 1: February 2025 |
| 12. | Language | English=en | en |
| 13. | Relation | Supp. Files | |
| 14. | Coverage | Geo-spatial location, chronological period, research sample (gender, age, etc.) | |
| 15. | Rights | Copyright and permissions |
Copyright (c) 2025 Fandi Presly Simamora, Ronsen Purba, Muhammad Fermi Pasha This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |