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INDONESIA
JURISMA: Jurnal Riset Bisnis & Manajemen
Published by Universitas Komputer Indonesia
ISSN : 20860455     EISSN : 2338929X     DOI : -
Core Subject : Economy, Science,
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance
JURISMA: Jurnal Riset Bisnis & Manajemen adalah wadah informasi berupa hasil peneltian, studi kepustakaan dalam rangka meningkatkan penelitian dan ilmu pengetahuan.
Arjuna Subject : -
Articles 12 Documents
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Search results for , issue "Vol. 12 No. 2: Oktober 2022" : 12 Documents clear
ANALISIS BIBLIOMETRIK ENTREPRENEURSHIP KORPORAT PADA BASIS DATA SCOPUS Purnomo, Margo; Ginanjar*, Jajang; Purbasari, Ratih; Paramita, Bunga; Nurdin, Mahmud
JURISMA : Jurnal Riset Bisnis & Manajemen Vol. 12 No. 2: Oktober 2022
Publisher : Program Studi Manajemen, Fakultas Ekonomi dan Bisnis, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jurisma.v12i2.7480

Abstract

Corporate Entrepreneurship (CE) has become an interesting area of ​​academic research today. This study aims to systematically analyze global trends and various current focus of CE research on CE and is expected to be a reference for CE researchers. The data is taken from the Scopus database with a time span of 2010-2020. Data were processed with Excel 2016 to analyze the main features of CE studies, including annual publication trends, authors, author's institution and country of origin, journals, references, and keywords. Data processing is then mapped visually using VOSviewer. The results of this study can provide a clear picture of the field of EK as well as can help academics to get focus on the direction of EK research in terms of exploitation and exploration in this field for future research. Keywords: Corporate Entrepreneurship, Bibliometric, VOSviewer, Scopus, Literature Review
CLOSING PRICE PREDICTION OF STOCK LISTED ON THE IRAQ STOCK EXCHANGE USING ANN-LSTM Al-Hasnawi, Salim Sallal; Al-Hchemi*, Laith Haleem
JURISMA : Jurnal Riset Bisnis & Manajemen Vol. 12 No. 2: Oktober 2022
Publisher : Program Studi Manajemen, Fakultas Ekonomi dan Bisnis, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jurisma.v12i2.8103

Abstract

Financial markets are highly reactive to events and situations, as seen by the very volatile movement of stock values. As a result, investors are having difficulties guessing prices and making investment decisions, especially when statistical techniques have failed to model historical prices. This paper aims to propose an RNNs-based predictive model using the LSTM model for predicting the closing price of four stocks listed on the Iraq Stock Exchange (ISX). The data used are historical closing prices provided by ISX for the period from 2/1/2019 to 24/12/2020. Several attempts were conducted to improve model training and minimize the prediction error, as models were evaluated using MSE, RMSE, and R2. The models performed with high accuracy in predicting closing price movement, despite the Intense volatility of time series. The empirical study concluded the possibility of relying on the RNN-LSTM model in predicting close prices at the ISX as well as decisions making upon. Keywords: Stock, LSTM, Prediction, ANN, RNN, ISX

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