IDEAS home Printed from https://ideas.repec.org/a/apa/ijbaas/2015p147-154.html
   My bibliography  Save this article

The Implementation of Fuzzy Logic to Predict the Bankruptcy of Company in Indonesia

Author

Listed:
  • EDNAWATI RAINARLI

    (University Of Computer Indonesia, Indonesia)

  • AURELIUS AARON

    (University Of Computer Indonesia, Indonesia)

Abstract

Prediction of bankruptcy of company is generally used to determine the risk of harm caused by inability of debtors in basic payment of its debt, interest rate, or both. In this research, it will be built on fuzzy model to predict bankruptcy of the company based on company’s characteristics in Indonesia. The data used would be obtained from the financial reports of public companies taken from the Indonesian Stock Exchange to do a correlation test. After correlation test would be conducted, it would be found that the financial ratios influence one year prior of bankruptcy and two year prior of bankruptcy. That ratios are used as parameter input of fuzzy model. The output of defuzzification of fuzzy model is a prediction of bankruptcy for each company. After conducted testing, we saw that fuzzy model can predict well the bankruptcy of 65 public companies to the year before bankruptcy and two years before bankruptcy, with the accuracy for each being 81,54% and 83,85%. Based on these results, fuzzy logic can be used as alternative to predict events in the future with a high degree of uncertainty especially for characteristic of the companies’ conditions in Indonesia.

Suggested Citation

  • Ednawati Rainarli & Aurelius Aaron, 2015. "The Implementation of Fuzzy Logic to Predict the Bankruptcy of Company in Indonesia," International Journal of Business and Administrative Studies, Professor Dr. Bahaudin G. Mujtaba, vol. 1(4), pages 147-154.
    • Handle: RePEc:apa:ijbaas:2015:p:147-154
    DOI: 10.20469/ijbas.1.10003-4
    as

    Download full text from publisher

    File URL: https://kkgpublications.com/business-volume-1-issue-4-article3/
    Download Restriction: no
    File URL: https://kkgpublications.com/wp-content/uploads/2019/04/IJBAS10003-4.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.20469/ijbas.1.10003-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Korol, Tomasz, 2013. "Early warning models against bankruptcy risk for Central European and Latin American enterprises," Economic Modelling, Elsevier, vol. 31(C), pages 22-30.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhao, Shuping & Xu, Kai & Wang, Zhao & Liang, Changyong & Lu, Wenxing & Chen, Bo, 2022. "Financial distress prediction by combining sentiment tone features," Economic Modelling, Elsevier, vol. 106(C).
    2. Chao Liu & Fengfeng Gao & Mengwan Zhang & Yuanrui Li & Cun Qian, 2024. "Reference Vector-Based Multiobjective Clustering Ensemble Approach for Time Series Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 181-210, July.
    3. Fatima Zahra Azayite & Said Achchab, 2019. "A hybrid neural network model based on improved PSO and SA for bankruptcy prediction," Papers 1907.12179, arXiv.org.
    4. du Jardin, Philippe, 2015. "Bankruptcy prediction using terminal failure processes," European Journal of Operational Research, Elsevier, vol. 242(1), pages 286-303.
    5. Tamara Ayœs, Armando Lenin & Villegas, Gladis Cecilia & Leones Castro, María Cristina & Salazar Bocanegra, Juan Antonio, 2018. "Modelaci—n del riesgo de insolvencia en empresas del sector salud empleando modelos logit || Modeling of Insolvency Risk in Health Sector Companies Using Logit Models," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 26(1), pages 128-145, Diciembre.
    6. Sumaira Ashraf & Elisabete G. S. Félix & Zélia Serrasqueiro, 2019. "Do Traditional Financial Distress Prediction Models Predict the Early Warning Signs of Financial Distress?," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    7. Petra Marešová & Lukáš Peter & Jan Honegr & Lukáš Režný & Marek Penhaker & Martin Augustýnek & Hana Mohelská & Blanka Klímová & Kamil Kuča, 2020. "Complexity Stage Model of the Medical Device Development Based on Economic Evaluation—MedDee," Sustainability, MDPI, vol. 12(5), pages 1-27, February.
    8. Spyridou, Anastasia, 2019. "Evaluating Factors of Small and Medium Hospitality Enterprises Business Failure: a conceptual approach," MPRA Paper 93997, University Library of Munich, Germany.
    9. Yali Cao & Yue Shao & Hongxia Zhang, 2022. "Study on early warning of E-commerce enterprise financial risk based on deep learning algorithm," Electronic Commerce Research, Springer, vol. 22(1), pages 21-36, March.
    10. Safaa Mrani & Loulid Adil, 2023. "Corporate failure : A literature review [La défaillance des entreprises : Une revue de littérature]," Post-Print hal-04219260, HAL.
    11. Amani, Farzaneh A. & Fadlalla, Adam M., 2017. "Data mining applications in accounting: A review of the literature and organizing framework," International Journal of Accounting Information Systems, Elsevier, vol. 24(C), pages 32-58.
    12. Duan, Yunlong & Mu, Chang & Yang, Meng & Deng, Zhiqing & Chin, Tachia & Zhou, Li & Fang, Qifeng, 2021. "Study on early warnings of strategic risk during the process of firms’ sustainable innovation based on an optimized genetic BP neural networks model: Evidence from Chinese manufacturing firms," International Journal of Production Economics, Elsevier, vol. 242(C).
    13. David Alaminos & Agustín del Castillo & Manuel Ángel Fernández, 2016. "A Global Model for Bankruptcy Prediction," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-18, November.
    14. Muñoz-Izquierdo, Nora & Segovia-Vargas, María Jesús & Camacho-Miñano, María-del-Mar & Pascual-Ezama, David, 2019. "Explaining the causes of business failure using audit report disclosures," Journal of Business Research, Elsevier, vol. 98(C), pages 403-414.
    15. Tomasz Korol, 2020. "Assessment of Trajectories of Non-bankrupt and Bankrupt Enterprises," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 1113-1135.
    16. Santosh Kumar Shrivastav & P. Janaki Ramudu, 2020. "Bankruptcy Prediction and Stress Quantification Using Support Vector Machine: Evidence from Indian Banks," Risks, MDPI, vol. 8(2), pages 1-22, May.
    17. Chien-Min Kang & Ming-Chieh Wang & Lin Lin, 2022. "Financial Distress Prediction of Cooperative Financial Institutions—Evidence for Taiwan Credit Unions," IJFS, MDPI, vol. 10(2), pages 1-25, April.
    18. Mirza, Nawazish & Rahat, Birjees & Naqvi, Bushra & Rizvi, Syed Kumail Abbas, 2023. "Impact of Covid-19 on corporate solvency and possible policy responses in the EU," The Quarterly Review of Economics and Finance, Elsevier, vol. 87(C), pages 181-190.
    19. Li, Hui & Hong, Lu-Yao & He, Jia-Xun & Xu, Xuan-Guo & Sun, Jie, 2013. "Small sample-oriented case-based kernel predictive modeling and its economic forecasting applications under n-splits-k-times hold-out assessment," Economic Modelling, Elsevier, vol. 33(C), pages 747-761.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:apa:ijbaas:2015:p:147-154. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Professor Dr. Bahaudin G. Mujtaba (email available below). General contact details of provider: https://kkgpublications.com/business/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.