PREDIKSI HARGA SAHAM PERUSAHAAN KELAPA SAWITMENGGUNAKAN PEMODELAN MLP DAN RBF

  • Linda Sari Dewi (1*) Sistem Informasi STMIK Nusa Mandiri

    • (*) Corresponding Author
Keywords: Multilayer Perceptron, MLP, Prediction, Radial Basis Function, RBF

Abstract

There is great demand estimation method to obtain accurate predictions of the future and use the predictions to the decision making process. This study aims to estimate the daily stock price PT. Astra Agro Lestari Tbk, Indonesia's crude oil company, using one of the promising alternative tool, the Neural Network. Two Neural Network model, namely Multilayer Perceptron (MLP) and Radial Basis Function (RBF). Various combinations of data preprocessing techniques, network topology, functions, and training algorithm is presented in order to obtain the best model. The empirical results show that neural networks Radial Basis Function provides the best forecasting accuracy than Multilayer Perceptron. 

References

G. Zhang, B. E. Patuwo, and M. Y. Hu, "Forecasting with artificial neural networks: the state of the art", International Journal of Forecasting, vol.14, 1998, pp.35-62.

P. H. Sherrod. (2010). DTREG – Predictive modeling software.

Rabunal, J. R., & Dorado, J. (2006). Artificial Neural Network in Real-Life Applications. United States of America: Idea Group Publishing.

Setiawan, W. (2008). Prediksi Harga Saham Menggunakan Jaringan Syaraf Tiruan Multilayer Feedforward Network Dengan Algoritma Backpropagation. Konferensi Nasional Sistem dan Informatika, 108-113.

Sureshkumar. (2012). Performance Analysis of Stock Price Prediction using Artificial Neural Network. Global Journal of Computer Science and Technology, 1-9.

Undang-Undang Republik Indonesia, (1995).

www.finance.yahoo.com
Published
2014-03-15
How to Cite
Dewi, L. (2014). PREDIKSI HARGA SAHAM PERUSAHAAN KELAPA SAWITMENGGUNAKAN PEMODELAN MLP DAN RBF. Jurnal Techno Nusa Mandiri, 11(1), 79-85. Retrieved from https://ejournal.nusamandiri.ac.id/index.php/techno/article/view/173
Article Metrics

Abstract viewed = 179 times
PDF downloaded = 204 times
Issue
Vol 11 No 1 (2014): Techno Nusa Mandiri : Journal of Computing and Information Technology Periode Maret 2014
Section
Articles
Copyright (c) 2014 Linda Sari Dewi

The copyright of any article in the TECHNO Nusa Mandiri Journal is fully held by the author under the Creative Commons CC BY-NC license.

  1. The copyright in each article belongs to the author.
  2. Authors retain all their rights to published works, not limited to the rights set out on this page.
  3. The author acknowledges that Techno Nusa Mandiri: Journal of Computing and Information Technology (TECHNO Nusa Mandiri) is the first to publish with a Creative Commons Attribution 4.0 International license (CC BY-NC).
  4. Authors can enter articles separately, manage non-exclusive distribution, from manuscripts that have been published in this journal into another version (for example: sent to author affiliation respository, publication into books, etc.), by acknowledging that the manuscript was published for the first time in Techno Nusa Mandiri: Journal of Computing and Information Technology (TECHNO Nusa Mandiri);
  5. The author guarantees that the original article, written by the stated author, has never been published before, does not contain any statements that violate the law, does not violate the rights of others, is subject to the copyright which is exclusively held by the author.
  6. If an article was prepared jointly by more than one author, each author submitting the manuscript warrants that he has been authorized by all co-authors to agree to copyright and license notices (agreements) on their behalf, and agrees to notify the co-authors of the terms of this policy. Techno Nusa Mandiri: Journal of Computing and Information Technology (TECHNO Nusa Mandiri) will not be held responsible for anything that may have occurred due to the author's internal disputes.