Comparison of Financial Distress Measurement Models in Technology Companies on the Indonesia Stock Exchange in 2022-2024
Abstract
The objectives of this study are: (1) to measure the potential financial distress of technology companies listed on the Indonesia Stock Exchange (IDX) during the 2022–2024 period using the Altman Z-Score, Zmijewski X-Score, and Grover G-Score methods; (2) to examine differences in the results among these methods; and (3) to determine the method with the highest level of accuracy. This study employs a quantitative approach using secondary data in the form of annual financial statements. The research sample consists of 29 companies with a total of 87 observations. The results of the analysis using the Altman Z-Score, Zmijewski X-Score, and Grover G-Score indicate that each method identifies three companies as potentially experiencing financial distress, with different company compositions across methods. The Kruskal–Wallis test results also show a statistically significant difference among the methods in predicting financial distress. Based on the accuracy test results, the Grover G-Score method is the most accurate method in this study. This research provides practical implications as an early warning tool for management and investors in assessing the risk of financial distress in technology companies.
Downloads
References
Altman, E. I. (1968). Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy. The Journal of Finance, 23(1), 589. https://doi.org/10.2307/2325319
Altman, E. I., Hotchkiss, E., & Wang, W. (2019). Corporate Financial distress, Restructuring, and Bankruptcy: Analyze Leveraged Finance, Distressed Debt, and Bankruptcy, Fourth Edition. In Strategic Management. https://doi.org/10.1093/oso/9780190090883.003.0009
Amin, N. F., Garancang, S., & Abunawa, K. (2023). Konsep Umum Populasi Dan Sampel Dalam Penelitian. Buku Ajar StatistikaJurnal Kajian Islam Kontemporer Dasar, 14(1), 15–31. https://doi.org/10.21070/2017/978-979-3401-73-7
Annisak, F., Sakinah Zainuri, H., & Fadilla, S. (2024). Peran Uji Hipotesis Penelitian Perbandingan Menggunakan Statistika Non Parametrik Dalam Penelitian. In AL ITTIHADU (Vol. 3, Issue 1). https://jurnal.asrypersadaquality.com/index.php/alittihadu
Arti, Y., & Ovami, D. C. (2022). Comparative Analysis of Altman’s Z Model and the Grover’s Model in Measuring the Health of Food And Beverages Companies on the Indonesia Stock Exchange. Jurnal Multidisiplin Madani, 2(2), 765–778. https://doi.org/10.54259/mudima.v2i2.432
Balasubramanian, S. A., Radhakrishna, G. S., Sridevi, P., & Natarajan, T. (2019). Modeling corporate financial distress using financial and non-financial variables: The case of Indian listed companies. International Journal of Law and Management, 61(3–4), 457–484. https://doi.org/10.1108/IJLMA-04-2018-0078
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 , Zmijewski Z - Score , and Grover G - Score. 390–398.
Colline, F. (2020). Bankruptcy Prediction Analysis: A Case Study of Retail Companies in Indonesia. 151(June 2017), 326–330. https://doi.org/10.2991/aebmr.k.200915.073
Farooq, U., Jibran Qamar, M. A., & Haque, A. (2018). A three-stage dynamic model of financial distress. Managerial Finance, 44(9), 1101–1116. https://doi.org/10.1108/MF-07-2017-0244
Isbahi, M. B., Zuana, M. M. M. ., & Mariana, E. R. . (2022). The Technology Strategy in Website Communication Media in Improving Business Activities. Majapahit Journal of Islamic Finance and Management, 1(2), 126–138. https://doi.org/10.31538/mjifm.v1i2.17
Liew, K. F., Lam, W. S., & Lam, W. H. (2023). Financial distress Analysis of Technology Companies Using Grover Model. 6. https://doi.org/10.3390/iocma2023-14405
Maninggarjati, E. R., Wulaningrum, R., Fitriana, R., & Putra, D. T. (2022). Financial distress Analysis of Coal Mining Companies. Proceedings of the International Conference on Applied Science and Technology on Social Science 2021 (ICAST-SS 2021), 647, 482–486. https://doi.org/10.2991/assehr.k.220301.079
Martini, R., Raihana Aksara, R., Rachma Sari, K., Zulkifli, Z., & Hartati, S. (2023). Comparison of Financial distress Predictions With Altman, Springate, Zmijewski, and Grover Models. Golden Ratio of Finance Management, 3(1), 11–21. https://doi.org/10.52970/grfm.v3i1.216
Nurfadillah, P. S., & Yulianti, E. (2024). Accuracy Analysis of the Financial distress Prediction Model Using Altman Z-Score, Springate, Zmijewski And Grover in the Oil, Gas and Geothermal Mining Subsectors Listed on the Indonesian Stock Exchange (BEI). Jurnal Ekonomi, 13(1), 2278–2290. https://doi.org/10.54209/ekonomi.v13i01
Oktafiraningsih, & Suryaningsum, S. (2024). Financial distress Prediction Analysis Using Altman Z-Score, Grover And Zmijewski Models In Property And Real Estate Sector Companies Listed On The Indonesia Stock Exchange For The 2020-2023 Period. 2(3), 204–211.
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. https://doi.org/10.1007/bf02755985
Pratiwi, M. R., Atmadjaja, Y. V. I., & Ferawati, I. W. (2023). Prediction Analysis of Company Bangkruptcy Using Comparison of the Altman Method (Z-Score) and Grover Method (G-scrore) as an Early Warning System in Pharmaceutical Subsector Companies. Jurnal Maksipreneur: Manajemen, Koperasi, Dan Entrepreneurship, 12(2), 486. https://doi.org/10.30588/jmp.v12i2.1472
Rahayu, S., Yudhawati, D., & Suharti, T. (2023). Analysis of Financial distress Predictions Using Altman (Z-Score), Zmijewski (X-Score) and Grover (G-Score) Methods. Manager : Jurnal Ilmu Manajemen, 6(4), 20–30. http://ejournal2.uika-bogor.ac.id/index.php/bidik/about
Reza, F., Dewi, C. K., & Yudhyani, E. (2021). Statistika Deskriptif Untuk Ekonomi & Bisnis. Tahta Media Group.
Salim, M. N., & Ismudjoko, D. (2021). An Analysis of Financial distress Accuracy Models in Indonesia Coal Mining Industry: An Altman, Springate, Zmijewski, Ohlson and Grover Approaches. Journal of Economics, Finance and Accounting Studies, 3(2), 01–12. https://doi.org/10.32996/jefas.2021.3.2.1
Spence, M. (1973). Job Market Signaling (Vol. 87, Issue 3, pp. 355–374).
Sudrajat, M. A., & Wijayanti, E. (2019). Analisis Prediksi Kebangkrutan (Financial distress) Dengan Perbandingan Model Altman, Zmijewski Dan Grover. Inventory: Jurnal Akuntansi, 3(2), 116. https://doi.org/10.25273/inventory.v3i2.5240
Wahyuni, I. A., Laba, A. R., & Rahim, F. R. (2024). Comparative Analysis of Altman Method Measurement , Springate , Zmijewski and Grover In Predicting Financial distress. 5(2), 674–687.
Winarso, E., Kusumah, R., Kartadjumena, E., Sherlita, E., & ... (2020). Comparison of Financial distress Analysis Using the “Z” Score Modification, X-Score, G-Score and S-Score Models To Analyze the …. 24(2), 7929–7954. https://repository.widyatama.ac.id/items/cf9b5654-9d7b-45a2-b26d-1b10940d722a
Zuana, M. M. M., Toha, M., & Isbahi, M. B. (2024). Exploration of Community Empowerment in a Village as the Entrance to a Lake in East Java. Malacca: Journal of Management and Business Development , 1(1), 47–55. https://doi.org/10.69965/malacca.v1i1.52
Copyright (c) 2026 Kezia Sugiwan, Fredella Colline
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
