Proceedings of the International Conference on Mathematics, Geometry, Statistics, and Computation (IC-MaGeStiC 2021)

Multiple Discriminant Analysis Altman Z-Score, Multiple Discriminant Analysis Stepwise and K-Means Cluster for Classification of Financial Distress Status in Manufacturing Companies Listed on the Indonesia Stock Exchange in 2019

Authors
Hazrina Ishmah*, Solimun, Maria Bernadetha Theresia Mitakda
Department of Statistics, Faculty of Mathematics and Natural Science, Brawijaya University, Malang, 65145, Indonesia
*Corresponding Email: hazrina_30@student.ub.ac.id
Corresponding Author
Hazrina Ishmah
Available Online 8 February 2022.
DOI
10.2991/acsr.k.220202.035How to use a DOI?
Keywords
Financial distress; K-means cluster; MDA Altman Z-score; MDA 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 the MDA Altman Z-Score method are the best variables for predicting financial distress status. MDA Altman Z-Score uses five variables from financial ratios. Variables used in Altman Z-Score 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 and validate that the MDA Altman Z-Score is appropriate in classifying manufacturing companies experiencing financial distress in 2019 using the K-Means cluster. 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.

Copyright
© 2022 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article under the CC BY-NC license.

Download article (PDF)

Volume Title
Proceedings of the International Conference on Mathematics, Geometry, Statistics, and Computation (IC-MaGeStiC 2021)
Series
Advances in Computer Science Research
Publication Date
8 February 2022
ISBN
10.2991/acsr.k.220202.035
ISSN
2352-538X
DOI
10.2991/acsr.k.220202.035How to use a DOI?
Copyright
© 2022 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Hazrina Ishmah
AU  - Solimun
AU  - Maria Bernadetha Theresia Mitakda
PY  - 2022
DA  - 2022/02/08
TI  - Multiple Discriminant Analysis Altman Z-Score, Multiple Discriminant Analysis Stepwise and K-Means Cluster for Classification of Financial Distress Status in Manufacturing Companies Listed on the Indonesia Stock Exchange in 2019
BT  - Proceedings of the  International Conference on Mathematics, Geometry, Statistics, and Computation (IC-MaGeStiC 2021)
PB  - Atlantis Press
SP  - 184
EP  - 189
SN  - 2352-538X
UR  - https://doi.org/10.2991/acsr.k.220202.035
DO  - 10.2991/acsr.k.220202.035
ID  - Ishmah2022
ER  -