Application of artificial neural network for predicting company financial performance in Indonesia stock exchange

Givaldi Ramadhan; Arian Dhini; Isti Surjandari Prajitno; Reggia Aldiana Wayasti

doi:10.1109/ICSITech.2017.8257118

Application of artificial neural network for predicting company financial performance in Indonesia stock exchange

Givaldi Ramadhan, Arian Dhini, Isti Surjandari Prajitno, Reggia Aldiana Wayasti

Department of Industrial Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

As the economy and financial market grow in Indonesia, the interest to invest and develop the market are steadily increasing. This provides an opportunity for company and investor to get more profit. The increasingly competitive market and dynamic condition require strategy to utilize investment. The ability to forecast company performance in financial sector is needed to keep up with the ever-growing market. The Artificial Neural Network (ANN) is one of the popular machine learning methods to be used as a forecasting method that requires a more complex model, uses more variable, and tends to be nonlinear. Hence, this method really suits to be adapted in financial sector, especially in the stock market. This study integrated the technical analysis and fundamental analysis together for the result. In addition, this study also shows that neural network as a predictive model could significantly outperform the minimum return.

Original language	English
Title of host publication	Proceeding - 2017 3rd International Conference on Science in Information Technology
Subtitle of host publication	Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017
Editors	Rafal Drezewski, Goutam Chakraborty, Shah Nazir, Lala Septem Riza, Ummi Raba'ah Hashim, Aji Prasetyo Wibawa, Yaya Wihardi, Andri Pranolo, Enjun Junaeti, Shi-Jinn Horng, Heui Seok Lim, Leonel Hernandez
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	241-245
Number of pages	5
ISBN (Electronic)	9781509058662
DOIs	https://doi.org/10.1109/ICSITech.2017.8257118
Publication status	Published - 12 Jan 2018
Event	3rd International Conference on Science in Information Technology, ICSITech 2017 - Bandung, Indonesia Duration: 25 Oct 2017 → 26 Oct 2017

Publication series

Name	Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017
Volume	2018-January

Conference

Conference	3rd International Conference on Science in Information Technology, ICSITech 2017
Country/Territory	Indonesia
City	Bandung
Period	25/10/17 → 26/10/17

Keywords

forecasting
neural network
stocks

Access to Document

10.1109/ICSITech.2017.8257118

Cite this

Ramadhan, G., Dhini, A., Prajitno, I. S., & Wayasti, R. A. (2018). Application of artificial neural network for predicting company financial performance in Indonesia stock exchange. In R. Drezewski, G. Chakraborty, S. Nazir, L. S. Riza, U. R. Hashim, A. P. Wibawa, Y. Wihardi, A. Pranolo, E. Junaeti, S.-J. Horng, H. S. Lim, & L. Hernandez (Eds.), Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017 (pp. 241-245). (Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSITech.2017.8257118

Ramadhan, Givaldi ; Dhini, Arian ; Prajitno, Isti Surjandari et al. / Application of artificial neural network for predicting company financial performance in Indonesia stock exchange. Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017. editor / Rafal Drezewski ; Goutam Chakraborty ; Shah Nazir ; Lala Septem Riza ; Ummi Raba'ah Hashim ; Aji Prasetyo Wibawa ; Yaya Wihardi ; Andri Pranolo ; Enjun Junaeti ; Shi-Jinn Horng ; Heui Seok Lim ; Leonel Hernandez. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 241-245 (Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017).

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title = "Application of artificial neural network for predicting company financial performance in Indonesia stock exchange",

abstract = "As the economy and financial market grow in Indonesia, the interest to invest and develop the market are steadily increasing. This provides an opportunity for company and investor to get more profit. The increasingly competitive market and dynamic condition require strategy to utilize investment. The ability to forecast company performance in financial sector is needed to keep up with the ever-growing market. The Artificial Neural Network (ANN) is one of the popular machine learning methods to be used as a forecasting method that requires a more complex model, uses more variable, and tends to be nonlinear. Hence, this method really suits to be adapted in financial sector, especially in the stock market. This study integrated the technical analysis and fundamental analysis together for the result. In addition, this study also shows that neural network as a predictive model could significantly outperform the minimum return.",

keywords = "forecasting, neural network, stocks",

author = "Givaldi Ramadhan and Arian Dhini and Prajitno, {Isti Surjandari} and Wayasti, {Reggia Aldiana}",

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doi = "10.1109/ICSITech.2017.8257118",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "241--245",

editor = "Rafal Drezewski and Goutam Chakraborty and Shah Nazir and Riza, {Lala Septem} and Hashim, {Ummi Raba'ah} and Wibawa, {Aji Prasetyo} and Yaya Wihardi and Andri Pranolo and Enjun Junaeti and Shi-Jinn Horng and Lim, {Heui Seok} and Leonel Hernandez",

booktitle = "Proceeding - 2017 3rd International Conference on Science in Information Technology",

address = "United States",

note = "3rd International Conference on Science in Information Technology, ICSITech 2017 ; Conference date: 25-10-2017 Through 26-10-2017",

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Ramadhan, G, Dhini, A , Prajitno, IS & Wayasti, RA 2018, Application of artificial neural network for predicting company financial performance in Indonesia stock exchange. in R Drezewski, G Chakraborty, S Nazir, LS Riza, UR Hashim, AP Wibawa, Y Wihardi, A Pranolo, E Junaeti, S-J Horng, HS Lim & L Hernandez (eds), Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017. Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 241-245, 3rd International Conference on Science in Information Technology, ICSITech 2017, Bandung, Indonesia, 25/10/17. https://doi.org/10.1109/ICSITech.2017.8257118

Application of artificial neural network for predicting company financial performance in Indonesia stock exchange. / Ramadhan, Givaldi; Dhini, Arian ; Prajitno, Isti Surjandari et al.
Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017. ed. / Rafal Drezewski; Goutam Chakraborty; Shah Nazir; Lala Septem Riza; Ummi Raba'ah Hashim; Aji Prasetyo Wibawa; Yaya Wihardi; Andri Pranolo; Enjun Junaeti; Shi-Jinn Horng; Heui Seok Lim; Leonel Hernandez. Institute of Electrical and Electronics Engineers Inc., 2018. p. 241-245 (Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Application of artificial neural network for predicting company financial performance in Indonesia stock exchange

AU - Ramadhan, Givaldi

AU - Dhini, Arian

AU - Prajitno, Isti Surjandari

AU - Wayasti, Reggia Aldiana

PY - 2018/1/12

Y1 - 2018/1/12

N2 - As the economy and financial market grow in Indonesia, the interest to invest and develop the market are steadily increasing. This provides an opportunity for company and investor to get more profit. The increasingly competitive market and dynamic condition require strategy to utilize investment. The ability to forecast company performance in financial sector is needed to keep up with the ever-growing market. The Artificial Neural Network (ANN) is one of the popular machine learning methods to be used as a forecasting method that requires a more complex model, uses more variable, and tends to be nonlinear. Hence, this method really suits to be adapted in financial sector, especially in the stock market. This study integrated the technical analysis and fundamental analysis together for the result. In addition, this study also shows that neural network as a predictive model could significantly outperform the minimum return.

AB - As the economy and financial market grow in Indonesia, the interest to invest and develop the market are steadily increasing. This provides an opportunity for company and investor to get more profit. The increasingly competitive market and dynamic condition require strategy to utilize investment. The ability to forecast company performance in financial sector is needed to keep up with the ever-growing market. The Artificial Neural Network (ANN) is one of the popular machine learning methods to be used as a forecasting method that requires a more complex model, uses more variable, and tends to be nonlinear. Hence, this method really suits to be adapted in financial sector, especially in the stock market. This study integrated the technical analysis and fundamental analysis together for the result. In addition, this study also shows that neural network as a predictive model could significantly outperform the minimum return.

KW - forecasting

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KW - stocks

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U2 - 10.1109/ICSITech.2017.8257118

DO - 10.1109/ICSITech.2017.8257118

M3 - Conference contribution

T3 - Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017

SP - 241

EP - 245

BT - Proceeding - 2017 3rd International Conference on Science in Information Technology

A2 - Drezewski, Rafal

A2 - Chakraborty, Goutam

A2 - Nazir, Shah

A2 - Riza, Lala Septem

A2 - Hashim, Ummi Raba'ah

A2 - Wibawa, Aji Prasetyo

A2 - Wihardi, Yaya

A2 - Pranolo, Andri

A2 - Junaeti, Enjun

A2 - Horng, Shi-Jinn

A2 - Lim, Heui Seok

A2 - Hernandez, Leonel

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 3rd International Conference on Science in Information Technology, ICSITech 2017

Y2 - 25 October 2017 through 26 October 2017

ER -

Ramadhan G, Dhini A , Prajitno IS, Wayasti RA. Application of artificial neural network for predicting company financial performance in Indonesia stock exchange. In Drezewski R, Chakraborty G, Nazir S, Riza LS, Hashim UR, Wibawa AP, Wihardi Y, Pranolo A, Junaeti E, Horng SJ, Lim HS, Hernandez L, editors, Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017. Institute of Electrical and Electronics Engineers Inc. 2018. p. 241-245. (Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017). doi: 10.1109/ICSITech.2017.8257118

Application of artificial neural network for predicting company financial performance in Indonesia stock exchange

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