Analysis of Precision Using the Altman Modification, Springate, Zmijewski, and Grover Model for Financial Distress Prediction

Jessica Magdalena, Toto Rusmanto


This study measures the accuracy of financial distress predictions by using the Zmijewski, Modified Altman, and Springate, Grover models. This research will take 2013-2017 as test data and compare it with the company's actual conditions in 2018 and 2019 to determine whether the three models can predict the company's financial difficulties to assess the accuracy of the model. This research was conducted using descriptive methods and quantitative approaches. This study took a sample of industries related to Real Estate and Property that were displayed on the Indonesia Stock Exchange (IDX) from 2013-2017 using a purposive sampling technique. Except for the modified Altman and Grover models, the results show discrepancies between the models and apparent accuracy from the 2018–2019 actuals and estimates for 2013–2017. The results of research conducted and tested using Stata 17 show that the model with the lowest accuracy is obtained by Springate with a score of 72%, type error I is 3%, and II is 26%. The second lowest model is obtained by the modified Altman model with a total score of 77% and type I error of 13%. The model with the second highest score was achieved by Grover with a score of 87% and type I error of 13%. The highest model in this test was achieved by Zmijewski with a model accuracy rate of 90% and type I and II errors of 5%.


Keywords: financial distress, the Altman modification, Springate, Zmijewski, Grover.



Full Text:



ABDU, E. (2022). Financial distress situation of financial sectors in Ethiopia: A review paper. Cogent Economics & Finance, 10(1), 1996020.

AFRIYADI, A.D. (2022). Waduh! Sederet Perusahaan Properti di RI Dinyatakan Pailit. detikFinance. Retrieved from

AL-KHALILI, S.S., & KADDUMI, T.A. (2022). Predicting Industrial Companies Financial Failure Using Sherrod and Zmijewski Models – Analytical Study. Journal of Southwest Jiaotong University, 57(4), 124-136.

BARNAS, B., WARDHANI, A.A.K., & MAYASARI, I. (2021). Prediksi Kebangkrutan pada PT Trikomsel Oke Tbk dengan Menggunakan Metode Altman Z-Score Modifikasi Periode 2012-2018. Indonesian Journal of Economics and Management, 1(2), 444-453.

DEWI, A., & HADRI, M. (2017). Financial distress prediction in Indonesia companies: finding an alternative model. Russian Journal of Agricultural and Socio-Economic Sciences, 61(1), 29-38.

HELASTICA, M., & PARAMITA, S. (2020). Analysis Financial Distress Prediction with Model Altman Z-Score, Zmijewski, and Grover in the Sub Sector Retail Listed on the Indonesian Stock Exchange (IDX) 2014-2018 Period. Proceedings of the International Conference on Environmental and Technology of Law, Business and Education on Post Covid 19, Bandar Lampung, 26 September 2020.

INAYATI, T., & YULIARINI, S. (2022). Prediksi Financial Distress Pada Perusahaan Perkebunan Kelapa Sawit Berbasis Syariah Di Indonesia. Jurnal Ilmiah Ekonomi Islam, 8(2), 1220-1228.

KISMAN, Z., & KRISANDI, D. (2019). How to Predict Financial Distress in the Wholesale Sector: Lesson from Indonesian Stock Exchange. Journal of Economics and Business, 2(3), 569-585.

KUSMARTONO, H., & RUSMANTO, T. (2022). Model prediksi kebangkrutan pada perusahaan perusahaan properti-konstruksi di Indonesia. SOSIOHUMANIORA: Jurnal Ilmiah Ilmu Sosial dan Humaniora, 8(2), 158-172.

LI, S., SHI, W., WANG, J., & ZHOU, H. (2021). A Deep Learning-Based Approach to Constructing a Domain Sentiment Lexicon: a Case Study in Financial Distress Prediction. Information Processing & Management, 58(5), 102673.

MILLATINA, Q.W., & NUGROHO, E.S. (2022). DER, TATO dan EPS pada Saham Perusahaan Otomotif dan Komponen di BEI periode 2015-2019. Journal of Economic, Management, Accounting and Technology, 5(1), 9-21.

NASUTION, S.A. (2019). Faktor yang Mempengaruhi Kondisi Financial Distress Perusahaan Property dan Real Estate. Owner, 3(1), 82-90.

PLATT, H.D., & PLATT, M.B. (2002). Predicting corporate financial distress: Reflections on choice-based sample bias. Journal of Economics and Finance, 26(2), 184-199.

RAHMAWATI, W. (2020). Hanson International (MYRX) dinyatakan pailit. Retrieved from

RIZKYANSYAH, K., & LAILY, N. (2018). Pengukuran Tingkat Kesehatan dan Gejala Financial Distress Dengan Metode Springate, Zmijewski, dan Grover. Jurnal Ilmu dan Riset Manajemen, 7(5), 1-16. Retrieved from

SAFRILIANA, R., SUBROTO, B., SUBEKTI, I., & RAHMAN, A.F. (2020). The Voluntary of Public Accountant Firms Switching with Modified Auditor’s Opinion as Mediation Variables. Journal of Southwest Jiaotong University, 55(6).

SINAGA, M.N., PELLENG, F.A., & MANGINDAAN, J.V. (2019). Analisis tingkat kebangkrutan pada perusahaan asuransi yang terdaftar di Bursa Efek Indonesia. Jurnal Administrasi Bisnis, 9(2), 28-36.

SUSANTI, N., LATIFA, I., & SUNARSI, D. (2020). The Effects of Profitability, Leverage, and Liquidity on Financial Distress on Retail Companies Listed on Indonesian Stock Exchange. Jurnal Ilmiah Ilmu Administrasi Publik, 10(1), 45-52.

TAHU, G.P. (2019). Predicting financial distress of construction companies in Indonesia: a comparison of Altman Z-score and Springate methods. International Journal of Sustainability, education, and Global Creative Economic, 2(2), 7-12.

WAHYUDI, H., PRASTYOWATI, A.H., WIDANINGGAR, N., R. & SAGARA, D.B. (2021). Altman Z-Score, Springate, and Zmijewski Methods’ Analysis for Predicting Financial Distress in Manufacturing Companies Listed on the Indonesia Stock Exchange. E-Proceeding Stie Mandala, The 3rd International Conference on Economics and Business 2021, 393-404. Retrieved from

WIRANTI, W., & MUNANDAR, A. (2021). Prediksi Financial Distress dengan Model Zmijewski dan Grover pada Perusahaan Retail yang Terdaftar di BEI Selama Tahun 2015-2019. Bahtera Inovasi, 5(1), 16-23.

WULANDARI, E.W., & JAENI, J. (2021). Faktor-Faktor Yang Mempengaruhi Financial Distress. Jurnal Ilmiah Universitas Batanghari Jambi, 21(2), 734-742.


  • There are currently no refbacks.