ANALISIS KOMPARATIF MODEL PREDIKSI FINANCIAL DISTRESS PADA PERUSAHAAN SUB-SEKTOR TEKSTIL DAN GARMEN YANG TERDAFTAR DI BURSA EFEK INDONESIA

Authors

  • M Indra Fauzi Universitas Pembangunan Nasional "Veteran" Jawa Timur
  • Rahman Amrullah Suwaidi Universitas Pembangunan Nasional "Veteran" Jawa Timur

DOI:

https://doi.org/10.34127/jrlab.v14i2.1540

Keywords:

Financial Distress, Altman Z-Score, Grover, Springate, Zmijewski

Abstract

Financial distress is a condition in which a company experiences a decline in financial performance, marked by decreasing profits and even potential losses. This study aims to identify the most accurate model in predicting financial distress in the textile and garment sub-sector in Indonesia. This study uses secondary data, collected from the companies’ financial statements published on the Indonesia Stock Exchange website and the respective company websites. The population in this study includes textile and garment sub-sector companies listed on the Indonesia Stock Exchange for the period 2019–2023, totaling 23 issuers. The sample was selected using purposive sampling, resulting in 20 companies being used as the research sample. This study compares the scores of four financial distress prediction models using statistical techniques, and evaluates the models’ accuracy by considering both the level of accuracy and error rate. The results show that the Springate model is the most accurate prediction model, with an accuracy rate of 95% and an error rate of 5%. Therefore, companies—especially those in the textile and garment sub-sector listed on the Indonesia Stock Exchange—can use the Springate model to predict financial distress. The researcher suggests that future studies consider using other models such as Ohlson, Taffler, or Internal Growth to enrich perspectives.

References

Altman, E. I. (1968). The Journal of FINANCE THE PREDICTION OF CORPORATE BANKRUPTCY.

Altman, E. I., Iwanicz-Drozdowska, M., Laitinen, E. K., & Suvas, A. (2017). Financial Dis-tress Prediction in an International Context: A Review and Empirical Analysis of Alt-man’s Z-Score Model. Journal of International Financial Management and Account-ing, 28(2), 131–171. https://doi.org/10.1111/jifm.12053

Arohmawati, P. P., & Pertiwi, T. K. (2021). PREDICTING OF FINANCIAL DISTRESS WITH THE ALTMAN Z-SCORE MODEL OF RETAIL COMPANIES LISTED ON IDX. In Balance: Jurnal Ekonomi (Vol. 17).

Asrulla, R., Jailani, M. S., & Jeka, F. (2023). Populasi dan sampling (kuantitatif), serta pem-ilihan informan kunci (kualitatif) dalam pendekatan praktis. https://www.researchgate.net/publication/386875018

Bunker, B., Ajit, I., Jacob, R. R., & Rajput, S. (2024). Analyzing financial distress in the automobile industry: a comparative study of Altman Z-Score, Springate S-Score, Zmi-jewski Z-Score, and Grover G-Score.

Fauzi, S. E., Sudjono, S., & Saluy, A. B. (2021). Comparative Analysis of Financial Sus-tainability Using the Altman Z-Score, Springate, Zmijewski and Grover Models for Companies Listed at Indonesia Stock Exchange Sub-Sector Telecommunication Period 2014 – 2019. Journal of Economics and Business, 4(1). https://doi.org/10.31014/aior.1992.04.01.321

Gunawan Putra As, A., Kartika Pertiwi, T., Studi Magister Manajemen, P., Ekonomi dan Bisnis, F., & Timur, J. (2021). Ciptaan disebarluaskan di bawah Lisensi Creative Commons Atribusi 4.0 Internasional. RASIO FUNDAMENTAL TERHADAP PER-TUMBUHAN LABA: VARIABEL MODERASI UKURAN PERUSAHAAN. Journal of Information System, Applied, Management, Accounting and Research. ( Printed), 5(1). http://journal.stmikjayakarta.ac.id/index.php/jisamar,

Kembi, L. D., Morasa, J., & Wokas, H. R. N. (2024). Comparative analysis of models (Alt-man, Grover, Zmijewski, Springate) in predicting company bankruptcy potential in the non-cyclical consumer sector. The Contrarian : Finance, Accounting, and Business Re-search, 3(2), 180–191. https://doi.org/10.58784/cfabr.165

Masnidar, N. L. (2017). Statistik Deskriptif.

Pramesti, A. W., & Yuniningsih, Y. (2023). Comparative Analysis of The Accuracy Level of The Zmijewski, Springate, and Grover Models to Predict Financial Distress. In Ameri-can Journal of Humanities and Social Sciences Research. www.ajhssr.com

Purwanto, E. (2020). Pengantar bisnis: Era revolusi industri 4.0.

Spence, M. (1978). JOB MARKET SIGNALING. In UNCERTAINTY in ECONOMICS: Readings and Exercises. https://doi.org/10.1016/B978-0-12-214850-7.50025-5

Sudaryanti, D., & Dinar, A. (2019). ANALISIS PREDIKSI KONDISI FINANCIAL DIS-TRESS MENGGUNAKAN RASIO LIKUIDITAS, PROFITABILITAS, FINAN-CIAL LEVERAGE DAN ARUS KAS. Jurnal Ilmiah Bisnis Dan Ekonomi Asia, 13(2), 101–110. https://doi.org/10.32812/jibeka.v13i2.120

Wicaksono, A. (2022). Metodologi Penelitian Pendidikan : Pengantar Ringkas. Garudha-waca.

Wijayanti, I., Nur, D. I., & Setyo, G. (2016). Ekuilibrium : Jurnal Ilmiah Bidang Ilmu Ekonomi ANALISIS NILAI PERUSAHAAN PADA SEKTOR PERTAMBANGAN BATUBARA DI BURSA EFEK INDONESIA. Ekuilibrium : Jurnal Ilmiah Bidang Ilmu Ekonomi, 11, 107–130. https://doi.org/https://doi.org/10.24269/ekuilibrium.v11i2.2016.pp107%20-%20130

Zalva Yunnafisah, A., Muhadjir Anwar, & Fani Khoirotunnisa. (2024). PERAN GCG DA-LAM MENGURANGI FINANCIAL DISTRESS: Dampak Penjualan dan Struktur Modal. Journal Publicuho, 7(4), 2011–2023. https://doi.org/10.35817/publicuho.v7i4.564

Zmijewski, M. E. (1984). Methodological Issues Related to the Estimation of Financial Dis-tress Prediction Models. In Studies on Current Econometric Issues in Accounting Re-search (Vol. 22).

Downloads

Published

2025-06-05