Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Andy Santoso
Universitas Multimedia Nusantara
Computer Science & IT Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Prediksi IHSG dengan Backpropagation Neural Network Andy Santoso; Seng Hansun
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 3 No 2 (2019): Agustus 2019
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (445.667 KB) | DOI: 10.29207/resti.v3i2.887

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.
Co-Authors Seng Hansun