PERBEDAAN MODEL OHLSON, MODEL TAFFLER DAN MODEL SPRINGATE DALAM MEMPREDIKSI FINANCIAL DISTRESS

Anny Widiasmara, Henny Catur Rahayu

Abstract


The purpose of this study is to provide empirical evidence that there are differences in the Ohlson, the Taffler and the Springate Model in predicting financial distress for companies listed on the Indonesia Stock Exchange in 2015-2017. The population in this study are all nine industrial sector companies listed. This study uses secondary data from annual financial reports / annual report in 2015-2017. Testing the hypothesis in this study using the normality test and the Kruskal Wallis test (different test). The results showed that the Taffler model is the model that has the highest level of accuracy in predicting financial distress conditions of companies listed on the Stock Exchange with an accuracy rate of 83.93%, then the Springate Model with an accuracy rate of 54.91% and the Ohlson Model which is a model with the lowest accuracy rate is 6.70%.

Keywords: Ohlson Model, Taffler Model, Springate Model, Financial Distress

Full Text:

PDF

References


Alali, M.S., Alawadhi, A.M., & Bash, A.Y. (2018). Predicting Bankruptcy Risk For Healthcare Companies Listed in Kuwait Stock Exchange Using Altman’s Z-Score Model. International Journal of Economics and Finance Research & Applications, Vol 2, Issue 1. Kuwait.

Fahmi, I. (2013). Analisis Laporan Keuangan. Bandung; Penerbit Alfabeta.

Ghozali, I. (2016). Aplikasi Analisis Multivariete dengan program IBM SPSS 23. Semarang: Badan Penerbit Universitas Diponegoro.

Gosh, B. (2017). Bankruptcy Modelling of Indian Public Sector Banks: Evidence From Neural Trace. International Journal of Applied Behavioral Economics. Volume 6. Issue 2. India: Institute of Management Christ University.

Hanafi, M.M. (2016). Manajemen Keuangan Edisi 2. Yogyakarta: BPFE-Anggota IKAPI.

Hariani, D.S. & Sujianto, A. (2017). Analisis Perbaandingan Model Altman, Model Springate dan Model Zmijewski dalam Memprediksi Kebangkrutan Bank Syariah di Indonesia. Inventory Jurnal Akuntansi, Vol 1. Madiun: Program Studi Akuntansi-FEB UNIPMA.

Indriyanti, M. (2019). The Accuracy of Financial Distress Prediction Models: Empirical Stidy on the World’s 25 Biggest Tech Companies in 2015-2016 Forbe’s Version. 3rd ICEEBA International Conference on Economics, Education, Business and Accounting. Surabaya: Accounting Department Faculty of Economy State University of Surabaya.

Jayanti, Q. & 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. Yogyakarta: Fakultas Ekonomi Universitas Atma Jaya.

Jouzbarkand, M., Aghajani, V., Khodadadi, M. & Sameni, F. (2012). Creation Bankcruptcy Prediction Model with Using Ohlson and Shirata Models. DOI: 10.7763/IPEDR. V54.1. Iran: Departement of Accounting Islamic Azad University.

Kadir. (2015). Statistika Terapan: Konsep, Contoh dan Analisis Data dengan Program SPSS/Lisrel dalam Penelitian Edisi Kedua. Jakarta: PT Rajagrafindo Persada.

Keown, Arthur J., Martin, John D., Petty, J. William., & Scott, David F. (2011). Manajemen Keuangan Prinsip dan Penerapan. Jakarta: PT Indeks.

Khoiriyah, S. (2019). Analisis Financial Distress, Perbandigan Dan Tingkat Akurasi Menggunakan Model Altman Z-Score, Grover, Springate Dan Zmijewski Untuk Memprediksi Kebangkrutan Pada Perusahaan (Studi Empiris Pada Perusahaan Delisting Di BEI Tahun 2012-2017). Skripsi. Surakarta: Jurusan Akuntansi Syariah Fakultas Ekonomi dan Bisnis Islam IAIN Surakarta.

Kusuma, R. (2017). Analisis Pengukuran Financial Distress Dengan Model Altman, Springate, Zmijewski, Ohlson, dan Grover Sebagai Early Warning System. Skripsi. Malang: Program Studi Manajemen Fakultas Ekonomi UIN Maulana Malik Ibrahim.

Margaretha, Farah. (2011). Manajemen Keuangan Untuk Manajer Non Keuangan. Jakarta: Penerbit Erlangga.

Meiliawati A. & Isharijadi (2016). Analisis Perbandingan Model Springate Dan Altman Z Score Terhadap Potensi Financial Distress (Studi Kasus Pada Perusahaan Sektor Kosmetik Yang Terdaftar Di Bursa Efek Indonesia). Jurnal Akuntansi dan Pendidikan, Volume %, Nomor 1. Madiun: IKIP PGRI Madiun.

Oz, I.O. & Yelkenci, T. (2015). The Generalizability of Financial Distress Prediction Models: Evidence from Turkey. Accounting and Management Information Systems Vol. 4, No. 4, pp, 685-703. United States & Turkey: Central Connecticut State University & Izmir University of Economics.

Perwira, Vincentus V. Y. (2016). Evaluasi Keakurasian Prediksi Kondisi Bankcrupty. Skripsi. Yogyakarta: Program Studi Akuntansi Fakultas Ekonomi Universitas Sanata Dharma.

Plihal, T., Sponerova, M. & Sponer, M. (2018). Comparative analysis Of Credit Risk Models In Relatoion To SME Segment. DOI:10.5817/FAI-1-3 No.1. Czech Republic: Faculty of Economics and Administration Department of Finance Masaryk Universuty & Department of Management Karel Englis College.

Priambodo, D. (2017). Analisis Perbandingan Model Altman, Springate, Grover, dan Smijewski dalam Memprediksi Fnancial Distress. Skripsi.


Article Metrics

Abstract has been read : 4255 times
PDF file viewed/downloaded: 0 times


DOI: http://doi.org/10.25273/inventory.v3i2.5242

Refbacks

  • There are currently no refbacks.


Copyright (c) 2019 Anny Widiasmara, Henny Catur Rahayu

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Indexed by:

                    

 

 

Supported by:

 

   

 

Editorial Office:

Universitas PGRI Madiun

Kampus 3 Lantai 2 Program Studi Akuntansi

Fakultas Ekonomi dan Bisnis

Jl. Auri no. 14-16 Madiun

 

 


Web Analytics Made Easy - StatCounter Inventory Stats