COMPARISON OF FINANCIAL DISTRESS ANALYSIS USING THE “Z” SCORE MODIFICATION, X-SCORE, G-SCORE AND S-SCORE MODELS TO ANALYZE THE ACCURACY OF THE BANKRUPTCY PREDICTION IN THE MINING INDUSTRY PERIOD OF 2016 – 2018
DOI:
https://doi.org/10.61841/ntmfrk22Keywords:
coal, financial distress, bankruptcy, Model Z ”score, Model X Score, Model G Score, Model S ScoreAbstract
Coal mining companies in Indonesia have a high business risk because most of the production is exported abroad, especially in China and India. The quality of coal in Indonesia is in the low category because it only produces 5,100 to 5,100 cal/gram. With fluctuations in world prices and unstable demand resulting in fluctuations in profits resulting in disrupted company performance, thus experiencing financial distress. In this study the researchers chose a coal mining company because of the number of companies listed in the stock exchange with 24 companies, and 4 of them did not announce their annual reports continuously, so that the companies studied were 20 companies from 2016 to 2018 company financial statement data, which were processed using the analysis model financial distress revealed by (1) Z "Altman Modification score, (2) X score from Zmijewski, (3) Model G score from Grover, and (4) S score from Grover to analyze the accuracy of bankruptcy predictions.
The results show that (1) there are differences in the accuracy of bankruptcy prediction between the Modified Z-Score Altman Model and the Springate S-Score Model for coal mining companies listed on the Stock Exchange in the 2016-2018 period. (2) There is a difference in the accuracy of bankruptcy prediction between the Modified Z-Score Altman Model and the Zmijewski X-Score on coal mining companies listed on the Stock Exchange in the 2016-2018 period. (3) There is a difference in the accuracy of bankruptcy prediction between the Modified Z"-Score Altman Model and the Grover G-Score Model for coal mining companies listed on the Stock Exchange in the 2016-2018 period. (4) There is a difference in the accuracy of bankruptcy prediction between the Springate S-Score Model and the Zmijewski X-Score in the coal mining companies listed on the Stock Exchange in the 2016-2018 period. (5) There is a difference in the accuracy of bankruptcy prediction between the S-Score Springate Model and the Grover G-Score Model in coal mining companies listed on the Stock Exchange in the 2016-2018 period. (6) There is a difference in the accuracy of bankruptcy prediction between Zmijewski's X-Score model and Grover's GScore model in coal mining companies listed on the Stock Exchange in the 2016-2018 period.
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[1] Abolfazl Aminian, dkk. 2016. Investigate the Ability of Bankruptcy Prediction Models of Altman and Springate and Zmijewski and Grover in Tehran Stock Exchange Mediterranean Journal of Social Sciences, MCSER Publishing, Rome-Italy, Vol. 7 No. 4 S1 July 2016.
[2] Acep Edison. 2018. Akuntansi Manajemen Edisi 2. Cendra: Bandung.
[3] Acep Edison. 2018. Metode Penelitian Edisi 2. Cendra: Bandung.
[4] Ayu Suci Ramadhani, Niki Lukviarman 2009. Perbandingan Analisis Prediksi Kebangkrutan Menggunakan Model Altman pertama, Altman revisi, dan Altman modifikasi dengan Ukuran dan Umur Perusahaan Sebagai Variabel Penjelas. Jurnal Siasat Bisnis. Hal: 15-28
[5] Bringham F., Eugene dan Joel F. Houston. 2014. Essentials of Financial Management, Third edition. Australia: CENGAGE
[6] Cooper, Donald R., and Pamela S. Schindler. 2014. Business Research Methods. 12. New York: The McGraw-Hill Companies, Inc.
[7] Danang, Sunyoto. 2013. Analisis Laporan Keuangan untuk Bisnis. Yogyakarta: Caps
[8] Darsono & Ashari. 2005. Pedoman Praktis Memahami Laporan Keuangan, Yogyakarta: Andi.
[9] Detiana dan Dinda Antika, 2012. Analisis kebangkrutan model Altman modifikasi Z-Scoore, Springate, Zmijewski, dan Ohlson pada perusahaan otomotif yang Go Public di Bursa Efek Indonesia (BEI)
[10] Diah Isti Ridha Buari. 2017. Analisis Tingkat Kebangkrutan Pada Perusahaan Manufaktur di Bursa Efek Indonesia (Studi Pada Perusahaan Yang Terdaftar di Bursa Efek Indonesia 2013-2015) Jurnal Bisnis dan Ekonomi (JBE), Maret 2017, Hal. 24–32, Vol. 24, No. 1.
[11] Enny Wahyu Puspita Sari. Penggunaan Model Zmijewski, Springate, Altman Z-Score Dan Grover Dalam Memprediksi Kepailitan Pada Perusahaan Transportasi Yang Terdaftar Di Bursa Efek Indonesia
[12] Fahmi, Irham. 2013. Analisis Laporan Keuangan. Bandung: Alfabeta.
[13] Firda Mastuti, dkk. 2013. Altman Z-Score Sebagai Salah Satu Metode Dalam Menganalisis Estimasi Kebangkrutan Perusahaan (Studi Pada Perusahaan Plastik dan Kemasan yang Terdaftar (Listing) di Bursa Efek Indonesia periode etahun 2010 sampai dengan 2012)
[14] Fitria Wulandari, dkk. 2017 Analisis Prediksi Kebangkrutan Menggunakan Metode Altman (Z-Score) Pada Perusahaan Farmasi (Studi Kasus Pada Perusahaan Yang Terdaftar Di Bursa Efek Indonesia Tahun 2011-2015). BENEFIT Jurnal Manajemen dan Bisnis Volume 2, Nomor 1, Juni 2017
[15] Ghodratollah Talebnia, dkk. 2016: Evaluating and comparing the ability to predict the bankruptcy prediction models of Zavgren and Springate in companies accepted on the Tehran Stock Exchange. Marketing and Branding Research 3(2016) 137-143
[16] Gitman, Lawrence J. 2003. Principles of managerial Finance, 10th edition, Boston: Addison-Wesley
[17] Hussain, H.I., Kamarudin, F., Thaker, H.M.T., & Salem, M.A. (2019). Artificial Neural Network to Model
Managerial Timing Decision: Non-Linear Evidence of Deviation from Target Leverage, International Journal of
Computational Intelligence Systems, 12 (2), 1282-1294.
[18] Harahap, Sofyan Syafri. 2009. “Analisis Kritis Atas Laporan Keuangan." Jakarta: Raja Grafindo Persada
[19] Hudah dan Lina Siti Nuril, 2011. Analisis perbandingan prediksi kabngkrutan model Altman modifikasi ZScoore Springate, Zmijewski, dan Ohlson pada perushaan manufaktur yang listing dalam swa 100
[20] Ikatan Akuntansi Indonesia. 2018. Standar Akuntansi Keuangan Efektif per 1 Januari 2018. Jakarta: Ikatan
Akuntan Indonesia.
[21] K.R. Subramanyam 2014. Analisis Laporan Keuangan, Buku 1, Edisi 11, Jakarta, Salemba Empat.
[22] K.R. Subramanyam dan John J. Wild 2010. Analisis Laporan Keuangan, Buku 2, Edisi 10, Jakarta, Salemba
Empat.
[23] Kasmir. 2014. Analisis Laporan Keuangan. Edisi Satu. Cetakan Ketujuh. Jakarta: PT Raja Grafindo Persada.
[24] Khalid Alkhatib and Ahmad Eqab Al Bzour. Predicting Corporate Bankruptcy of Jordanian-Listed Companies:
Using Altman and Kida Models 2011 International Journal of Business and Management, Vol. 6, No. 3; March
2011.
[25] Lesmana, Rico, and Surjanto, Rudy 2003. Financial Performance Analyzing. Jakarta: Elex Meddia Komputindo.
[26] Mardiasmo, 2007. Akuntansi Keuangan Dasar, edisi ke dua, penerbit BPFEUGM, Yogyakarta.
[27] Muammar Khaddafi, Dkk. (2017) Analysis Z-score to Predict Bankruptcy in Banks Listed in Indonesia Stock
Exchange. International Journal of Economics and Financial Issues, 2017, 7(3), 326-330.
[28] Ni Made Evi Dwi Prihanthini, Maria M. Ratna Sari (2013). Prediksi Kebangkrutan Dengan Model Grover,
Altman Z-Score, Springate Dan Zmijewski Pada Perusahaan Food And Beverage Di Bursa Efek Indonesia. EJurnal Akuntansi Universitas Udayana 5.2 (2013): 417-435.
[29] Nur Hasbullah Matturungan, dkk. (2017). Manufacturing Company Bankruptcy Prediction in Indonesia With the Altman Z-Score Model (2017). Jurnal of Applied Management (JAM) Volume 15 Number 1, March 2017 Indexed in Google Scholar.
[30] Peyman Imanzadeh, dkk. (2011). A Study of the Application of Springate and Zmijewski Bankruptcy Prediction Models in Firms Accepted in Tehran Stock Exchange. Australian Journal of Basic and Applied Sciences, 5(11): 1546-1550, 2011
[31] Queenaria Jayanti, Rustiana, 2015. Analisis Tingkat Akurasi Model: model Prediksi Kebangkrutan untuk memprediksi voluntary auditor switching (Studi pada perusahaan manufaktur yang terdaftar di BEI). MODUS Vol. 27 (2): 87-108
[32] Qunfeng Liao, Seyed Mehdian (2016). Measuring Financial Distress and Predicting Corporate Bankruptcy: An Index Approach. REBS Volume 9, Issue 1, pp. 33-51, 2016
[33] Salamat, S., Lixia, N. Naseem, S., Muhammad Mohsin, M., Zia-ur-Rehman, M., Baig, S.A. 2020. Modeling cryptocurrencies volatility using Garch models: a comparison based on Normal and Student’s T-Error distribution. Entrepreneurship and Sustainability Issues, 7(3), 1580-1596. https://doi.org/10.9770/jesi.2020.7.3(11)
[34] S. Munawir. 2007. Analisis Laporan Keuangan, Edisi Empat. Yogyakarta: PT. Liberty.
[35] Sartono Agus. 2010. Manejemen Keuangan Teori dan Aplikasi. Edisi 4. BPFE: Yogyakarta.
[36] Sekaran, Uma, and Roger Bougie. 2016. Research Methods for Business: A Skill-Building Approach. Edisi 7. Chichester: Wiley.
[37] Surapol Pongsatat, dkk. (2004). Bankruptcy Prediction for Large and Small Firms in Asia: A Comparison of Ohlson and Altman. Journal of Accounting and Corporate Governance Volume 1 Number 2, December 2004 pp. 1-13
[38] Syamsul Hadi, Atika Anggraeni. Pemilihan Prediktor Delisting Terbaik (Perbandingan Antara the Zmijewski Model, the Altman Model, and Dan The Springate Model)
[39] Subramanyam K.R., Financial Statement Analysis, Eleventh edition, Mc Graw-Hill International Edition, 2009
[40] Tokhayeva, Z.O., Almukhambetova, B.Z., Keneshbayev, B., Akhmetova, K. 2020. Innovative processes’ management in agriculture and food security: development opportunities. Entrepreneurship and Sustainability Issues, 7(3), 1565-1579. https://doi.org/10.9770/jesi.2020.7.3(10)
[41] DMD. (2016). Perusahaan Besar Bangkrut di Indonesia. Dikutip dari: https://ekbis.sindonews.com/read/1085897/39/perusahaan-besar-bangkrut-di-indonesia-1455640928 Diakses pada 5 maret 2018 (Pukul 15.45)
[42] IDX. (2019) Laporan keuangan dan Tahunan. Dikutip dari: https://www.idx.co.id/
[43] https://www.indonesia-investments.com/id/bisnis/komoditas/batu-bara/item236
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