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FORECASTING SAHAM SYARIAH DENGAN MENGGUNAKAN LSTM

Al-Masraf: Jurnal Lembaga Keuangan Perbankan

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Field Value
 
Title FORECASTING SAHAM SYARIAH DENGAN MENGGUNAKAN LSTM
 
Creator FAUZI, AHMAD
 
Subject Financial Institutions and Banks
Forecasting, LSTM, Islamic Stock
 
Description Islamic stocks as one of the many stocks listed on the JCI are a barometer of the Islamic market in Indonesia. One approach in predicting stock prices is by using machine learning. The purpose of this study is to make a model that is used to predict JII shares using the LSTM approach. The data used amounted to 1402 records related to the Jakarta Islamic Index (JII) stock from March 4, 2014 - January 2, 2019. Model making uses 3 Epochs (1, 10 and 20). The results showed the best model was to use 20 Epochs. The increase in Epoch affects the value of MSE and RMSE which are getting smaller. For Epoch 20, the values of MSE and RMSE are ~ 0.00019 and ~ 0.014, respectively.
 
Publisher Prodi Manaj. Perbankan Syariah Fakultas Ekonomi dan Bisnis Islam – UIN Imam Bonjol Padang
 
Contributor —
 
Date 2019-06-30
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Survey/Interview
 
Format application/pdf
 
Identifier http://journal.febi.uinib.ac.id/index.php/almasraf/article/view/235
10.15548/al-masraf.v4i1.235
 
Source Al-Masraf : Jurnal Lembaga Keuangan dan Perbankan; Vol 4, No 1 (2019): Januari - Juni 2019; 65-69
2528-5637
2528-5629
 
Language ind
 
Relation http://journal.febi.uinib.ac.id/index.php/almasraf/article/view/235/253
http://journal.febi.uinib.ac.id/index.php/almasraf/article/downloadSuppFile/235/FORECASTING%20SAHAM%20SYARIAH%20DENGAN%20MENGGUNAKAN%20LSTM
 
Rights Copyright (c) 2019 Al-Masraf : Jurnal Lembaga Keuangan dan Perbankan
http://creativecommons.org/licenses/by-nc-sa/4.0