Classification of financial distress status in manufacturing companies listed on the Indonesia stock exchange in 2019 with multiple discriminant analysis altman z-score and multiple discriminant analysis stepwise

Hazrina Ishmah; S. Solimun; Maria Bernadetha Theresia Mitakda

doi:10.1063/5.0187181

Classification of financial distress status in manufacturing companies listed on the Indonesia stock exchange in 2019 with multiple discriminant analysis altman z-score and multiple discriminant analysis stepwise

Hazrina Ishmah^*
, S. Solimun
, Maria Bernadetha Theresia Mitakda

^*Corresponding author for this work

Faculty of Mathematics and Natural Sciences

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

Abstract

This study uses the MDA (Multiple Discriminant Analysis) Altman Z-Score to predict the status of financial distress in manufacturing companies listed on the Indonesia Stock Exchange in 2019. MDA Stepwise model is used to prove that the variables used in Altman Z-Score method are best variables for predicting financial distress. MDA Altman Z-Score uses five variables from financial ratios are working capital/total assets, retained earnings/total assets, earnings before interest and taxes/total assets, market value equility/book value of total liabilities and sales/total assets. The variables used in MDA Stepwise are 38 financial ratios. In this study, the results obtained for the best prediction of financial distress status using MDA Stepwise seen from the highest accuracy value (84.54%) and significant variables in predicting financial distress status are capital market to book value of debt, sales/work capital, and sales/current assets variables. The best classification for manufacturing companies if they are classified into 3 groups, namely the group not experiencing financial distress, gray area and experiencing financial distress. The category of the grouping of companies resulted in 73 companies experiencing financial distress one company was in the gray area and nine companies did not experience financial distress.

Original language	English
Title of host publication	AIP Conference Proceedings
Editors	Minetaka Sugiyama, Marcelo Ornaghi Orlandi, Arief Gusnanto, Walid Fouad, Fadzilah Adibah Abdul Majid, Poedji Loekitowati Hariani, Muhammad Said, Robbi Rahim
Publisher	American Institute of Physics Inc.
Edition	1
ISBN (Electronic)	9780735447752
DOIs	https://doi.org/10.1063/5.0187181
Publication status	Published - 28 Dec 2023
Event	2nd Sriwijaya International Conference of Basic and Applied Sciences 2021, SICBAS 2021 - Palembang, Indonesia Duration: 2 Nov 2021 → …

Publication series

Name	AIP Conference Proceedings
Number	1
Volume	2913
ISSN (Print)	0094-243X
ISSN (Electronic)	1551-7616

Conference

Conference	2nd Sriwijaya International Conference of Basic and Applied Sciences 2021, SICBAS 2021
Country/Territory	Indonesia
City	Palembang
Period	2/11/21 → …

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure
SDG 17 Partnerships for the Goals

Keywords

Financial Distress
MDA Altman Z-Score
MDA Stepwise.

Access to Document

10.1063/5.0187181

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Ishmah, H., Solimun, S., & Mitakda, M. B. T. (2023). Classification of financial distress status in manufacturing companies listed on the Indonesia stock exchange in 2019 with multiple discriminant analysis altman z-score and multiple discriminant analysis stepwise. In M. Sugiyama, M. O. Orlandi, A. Gusnanto, W. Fouad, F. A. A. Majid, P. L. Hariani, M. Said, & R. Rahim (Eds.), AIP Conference Proceedings (1 ed.). Article 030022 (AIP Conference Proceedings; Vol. 2913, No. 1). American Institute of Physics Inc.. https://doi.org/10.1063/5.0187181

Ishmah, Hazrina ; Solimun, S. ; Mitakda, Maria Bernadetha Theresia. / Classification of financial distress status in manufacturing companies listed on the Indonesia stock exchange in 2019 with multiple discriminant analysis altman z-score and multiple discriminant analysis stepwise. AIP Conference Proceedings. editor / Minetaka Sugiyama ; Marcelo Ornaghi Orlandi ; Arief Gusnanto ; Walid Fouad ; Fadzilah Adibah Abdul Majid ; Poedji Loekitowati Hariani ; Muhammad Said ; Robbi Rahim. 1. ed. American Institute of Physics Inc., 2023. (AIP Conference Proceedings; 1).

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title = "Classification of financial distress status in manufacturing companies listed on the Indonesia stock exchange in 2019 with multiple discriminant analysis altman z-score and multiple discriminant analysis stepwise",

abstract = "This study uses the MDA (Multiple Discriminant Analysis) Altman Z-Score to predict the status of financial distress in manufacturing companies listed on the Indonesia Stock Exchange in 2019. MDA Stepwise model is used to prove that the variables used in Altman Z-Score method are best variables for predicting financial distress. MDA Altman Z-Score uses five variables from financial ratios are working capital/total assets, retained earnings/total assets, earnings before interest and taxes/total assets, market value equility/book value of total liabilities and sales/total assets. The variables used in MDA Stepwise are 38 financial ratios. In this study, the results obtained for the best prediction of financial distress status using MDA Stepwise seen from the highest accuracy value (84.54\%) and significant variables in predicting financial distress status are capital market to book value of debt, sales/work capital, and sales/current assets variables. The best classification for manufacturing companies if they are classified into 3 groups, namely the group not experiencing financial distress, gray area and experiencing financial distress. The category of the grouping of companies resulted in 73 companies experiencing financial distress one company was in the gray area and nine companies did not experience financial distress.",

keywords = "Financial Distress, MDA Altman Z-Score, MDA Stepwise.",

author = "Hazrina Ishmah and S. Solimun and Mitakda, \{Maria Bernadetha Theresia\}",

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language = "English",

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Ishmah, H, Solimun, S & Mitakda, MBT 2023, Classification of financial distress status in manufacturing companies listed on the Indonesia stock exchange in 2019 with multiple discriminant analysis altman z-score and multiple discriminant analysis stepwise. in M Sugiyama, MO Orlandi, A Gusnanto, W Fouad, FAA Majid, PL Hariani, M Said & R Rahim (eds), AIP Conference Proceedings. 1 edn, 030022, AIP Conference Proceedings, no. 1, vol. 2913, American Institute of Physics Inc., 2nd Sriwijaya International Conference of Basic and Applied Sciences 2021, SICBAS 2021, Palembang, Indonesia, 2/11/21. https://doi.org/10.1063/5.0187181

Classification of financial distress status in manufacturing companies listed on the Indonesia stock exchange in 2019 with multiple discriminant analysis altman z-score and multiple discriminant analysis stepwise. / Ishmah, Hazrina; Solimun, S.; Mitakda, Maria Bernadetha Theresia.
AIP Conference Proceedings. ed. / Minetaka Sugiyama; Marcelo Ornaghi Orlandi; Arief Gusnanto; Walid Fouad; Fadzilah Adibah Abdul Majid; Poedji Loekitowati Hariani; Muhammad Said; Robbi Rahim. 1. ed. American Institute of Physics Inc., 2023. 030022 (AIP Conference Proceedings; Vol. 2913, No. 1).

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

TY - GEN

T1 - Classification of financial distress status in manufacturing companies listed on the Indonesia stock exchange in 2019 with multiple discriminant analysis altman z-score and multiple discriminant analysis stepwise

AU - Ishmah, Hazrina

AU - Solimun, S.

AU - Mitakda, Maria Bernadetha Theresia

PY - 2023/12/28

Y1 - 2023/12/28

N2 - This study uses the MDA (Multiple Discriminant Analysis) Altman Z-Score to predict the status of financial distress in manufacturing companies listed on the Indonesia Stock Exchange in 2019. MDA Stepwise model is used to prove that the variables used in Altman Z-Score method are best variables for predicting financial distress. MDA Altman Z-Score uses five variables from financial ratios are working capital/total assets, retained earnings/total assets, earnings before interest and taxes/total assets, market value equility/book value of total liabilities and sales/total assets. The variables used in MDA Stepwise are 38 financial ratios. In this study, the results obtained for the best prediction of financial distress status using MDA Stepwise seen from the highest accuracy value (84.54%) and significant variables in predicting financial distress status are capital market to book value of debt, sales/work capital, and sales/current assets variables. The best classification for manufacturing companies if they are classified into 3 groups, namely the group not experiencing financial distress, gray area and experiencing financial distress. The category of the grouping of companies resulted in 73 companies experiencing financial distress one company was in the gray area and nine companies did not experience financial distress.

AB - This study uses the MDA (Multiple Discriminant Analysis) Altman Z-Score to predict the status of financial distress in manufacturing companies listed on the Indonesia Stock Exchange in 2019. MDA Stepwise model is used to prove that the variables used in Altman Z-Score method are best variables for predicting financial distress. MDA Altman Z-Score uses five variables from financial ratios are working capital/total assets, retained earnings/total assets, earnings before interest and taxes/total assets, market value equility/book value of total liabilities and sales/total assets. The variables used in MDA Stepwise are 38 financial ratios. In this study, the results obtained for the best prediction of financial distress status using MDA Stepwise seen from the highest accuracy value (84.54%) and significant variables in predicting financial distress status are capital market to book value of debt, sales/work capital, and sales/current assets variables. The best classification for manufacturing companies if they are classified into 3 groups, namely the group not experiencing financial distress, gray area and experiencing financial distress. The category of the grouping of companies resulted in 73 companies experiencing financial distress one company was in the gray area and nine companies did not experience financial distress.

KW - Financial Distress

KW - MDA Altman Z-Score

KW - MDA Stepwise.

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M3 - Conference contribution

AN - SCOPUS:85181810348

T3 - AIP Conference Proceedings

BT - AIP Conference Proceedings

A2 - Sugiyama, Minetaka

A2 - Orlandi, Marcelo Ornaghi

A2 - Gusnanto, Arief

A2 - Fouad, Walid

A2 - Majid, Fadzilah Adibah Abdul

A2 - Hariani, Poedji Loekitowati

A2 - Said, Muhammad

A2 - Rahim, Robbi

PB - American Institute of Physics Inc.

T2 - 2nd Sriwijaya International Conference of Basic and Applied Sciences 2021, SICBAS 2021

Y2 - 2 November 2021

ER -

Ishmah H, Solimun S, Mitakda MBT. Classification of financial distress status in manufacturing companies listed on the Indonesia stock exchange in 2019 with multiple discriminant analysis altman z-score and multiple discriminant analysis stepwise. In Sugiyama M, Orlandi MO, Gusnanto A, Fouad W, Majid FAA, Hariani PL, Said M, Rahim R, editors, AIP Conference Proceedings. 1 ed. American Institute of Physics Inc. 2023. 030022. (AIP Conference Proceedings; 1). doi: 10.1063/5.0187181

Classification of financial distress status in manufacturing companies listed on the Indonesia stock exchange in 2019 with multiple discriminant analysis altman z-score and multiple discriminant analysis stepwise

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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