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Abstract

Penelitian ini bertujuan untuk memberikan gambaran mengenai kondisi financial distress pada masing-masing sektor perusahaan non keuangan di Indonesia periode 2014-2018. Sampel penelitian sebanyak 1.865 yang diperoleh melalui metode purposive sampling. Teknik analisis data menggunakan analisis statistik deskriptif. Hasil penelitian menunjukkan bahwa perusahaan di sektor infrastruktur, utilitas dan transportasi serta berbagai sektor industri mengalami financial distress. Perusahaan di sektor pertanian, sektor industri dasar dan kimia, serta sektor pertambangan berada di wilayah abu-abu atau kondisi yang rentan mengalami financial distress. Perusahaan di sektor properti, real estate dan konstruksi bangunan, sektor industri barang konsumsi serta sektor perdagangan, jasa dan investasi berada dalam kondisi keuangan yang baik dan memiliki kemungkinan kecil mengalami financial distress.

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References

  1. Abbas, D. S., & Sari, P. A. (2019). Pengaruh Likuiditas, Komisaris Independen, Kepemilikan Institusional dan Ukuran Perusahaan terhadap Financial Distress. Jurnal Ilmiah Akuntansi Universitas Pamulang, 7(2), 119– 127.
  2. Agrawal, K., & Maheshwari, Y. (2019). Efficacy of industry factors for corporate default prediction. IIMB Management Review, 31(1), 71–77. https://doi.org/10.1016/j.iimb.2018.08.007
  3. Altman, E. I. (1968). Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankcrupty. The Journal of Finance, XXIII(1), 589–609. https://doi.org/10.1111/j.1540-6261.1946.tb01544.x
  4. Altman, E. I., & Hotchkiss, E. (2006). Corporate Financial Distress and Bankruptcy: Predict and Avoid Bankruptcy, Analyze and Invest in Distressed Debt. In Wiley Finance (Third Edit). Wiley Finance. https://doi.org/10.1561/0500000009
  5. Asmarani, S. A., & Lestari, D. (2018). Analisis Pengaruh Likuiditas , Leverage dan Profitabilitas Terhadap
  6. 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
  7. Barboza, F., Kimura, H., & Altman, E. (2017). Machine learning models and bankruptcy prediction. Expert Systems with Applications, 83, 405–417. https://doi.org/10.1016/j.eswa.2017.04.006
  8. Beaver, W. H. (1966). Financial Ratios As Predictors Of Failure. Journal of Accounting Research, 4(1966), 71– 111.
  9. Ben Jabeur, S. (2017). Bankruptcy prediction using Partial Least Squares Logistic Regression. Journal of Retailing and Consumer Services, 36(February), 197–202. https://doi.org/10.1016/j.jretconser.2017.02.005
  10. Boratyńska, K., & Grzegorzewska, E. (2018). Bankruptcy Prediction In The Agribusiness Sector: Lessons From Quantitative And Qualitative Approaches. Journal of Business Research, 89(February), 175–181. https://doi.org/10.1016/j.jbusres.2018.01.028
  11. Charalambakis, E. C., & Garrett, I. (2019). On corporate financial distress prediction: What can we learn from private firms in a developing economy? Evidence from Greece. Review of Quantitative Finance and Accounting, 52(2), 467–491. https://doi.org/10.1007/s11156-018-0716-7
  12. Choi, H., Son, H., & Kim, C. (2018). Predicting financial distress of contractors in the construction industry using ensemble learning. Expert Systems with Applications, 110, 1–44. https://doi.org/10.1016/j.eswa.2018.05.026
  13. Chou, C. H., Hsieh, S. C., & Qiu, C. J. (2017). Hybrid genetic algorithm and fuzzy clustering for bankruptcy prediction. Applied Soft Computing Journal, 56, 298–316. https://doi.org/10.1016/j.asoc.2017.03.014
  14. Damayanti, N. D., & Kusumaningtyas, R. (2020). Pengaruh Corporate Governance terhadap Financial Distress pada Sektor Perusahaan Jasa Infrastruktur, Utilitas dan TRansportasi di Bursa Efek Indonesia Periode 2015- 2017. AKUNESA: Jurnal Akuntansi Unesa, 8(3).
  15. Dance, M., & Made, S. I. (2019). Financial Ratio Analysis in Predicting Financial Conditions Distress in Indonesia Stock Exchange. Russian Journal of Agricultural and Socio-Economic Sciences, 86(2), 155–165. https://doi.org/10.18551/rjoas.2019-02.18
  16. Dewi, A. R. S., & Wahyuliana, E. (2019). Analysis of profit performance and asset management to financial distress bakrie group company listing in Indonesia stock exchange. International Journal of Scientific and Technology Research, 8(3), 106–110.
  17. Donald R. Cooper, & Pamela S. Schindler. (2014). Business Research Methods (Twelfth Ed). McGraw-Hill/Irwin.
  18. García, V., Marqués, A. I., Sánchez, J. S., & Ochoa-Domínguez, H. J. (2019). Dissimilarity-Based Linear Models for Corporate Bankruptcy Prediction. Computational Economics, 53(3), 1019–1031. https://doi.org/10.1007/s10614-017-9783-4
  19. Geng, R., Bose, I., & Chen, X. (2015). Prediction of financial distress: An empirical study of listed Chinese companies using data mining. In European Journal of Operational Research (Vol. 241, Issue 1). Elsevier B.V. https://doi.org/10.1016/j.ejor.2014.08.016
  20. Giannopoulos, G., & Sigbjørnsen, S. (2019). Prediction of Bankruptcy Using Financial Ratios in the Greek Market.
  21. Theoretical Economics Letters, 09(04), 1114–1128. https://doi.org/10.4236/tel.2019.94072
  22. Ginanjar, Y. (2018). Financial Distress pada Perspektif Operating Capacity, Profitabilitas dan Leverage (Studi pada Perusahaan Manufaktur Sektor Industri Barang Konsumsi yang terdaftar di Bursa Efek Indonesia Periode 2013-2015. MAKSI: Jurnal Ilmiah Manajemen & Akuntansi, 5(2), 91–100.
  23. Harianti, R., & Paramita, R. A. S. (2019). Analisis faktor internal terhadap financial distress sektor perdagangan, jasa, dan investasi yang go public pada periode 2013 - 2017. Jurnal Ilmu Manajemen, 7(4), 984–993.
  24. Hosaka, T. (2018). Bankruptcy prediction using imaged financial ratios and convolutional neural networks. Expert Systems with Applications, 117, 287–299. https://doi.org/10.1016/j.eswa.2018.09.039
  25. Jayasekera, R. (2018). Prediction Of Company Failure: Past, Present And Promising Directions For The Future.
  26. International Review of Financial Analysis, 55, 196–208. https://doi.org/10.1016/j.irfa.2017.08.009
  27. Karugu, C., Achoki, G., & Kiriri, P. (2018). Capital Adequacy Ratios as Predictors of Financial Distress in Kenyan Commercial Banks. Journal of Financial Risk Management, 07(03), 278–289. https://doi.org/10.4236/jfrm.2018.73018
  28. Khoja, L., Chipulu, M., & Jayasekera, R. (2019). Analysis of financial distress cross countries: Using macroeconomic, industrial indicators and accounting data. International Review of Financial Analysis, 66(February), 101379. https://doi.org/10.1016/j.irfa.2019.101379
  29. 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. https://doi.org/10.31014/aior.1992.02.03.109
  30. Klepac, V., & Hampel, D. (2017). Predicting financial distress of agriculture companies in EU. Agricultural Economics (Czech Republic), 63(8), 347–355. https://doi.org/10.17221/374/2015-AGRICECON
  31. Kulsum, M. puji. (2020). Nominal: Barometer Riset Akuntansi dan Manajemen. Nominal: Barometer Riset Akuntansi Dan Manajemen, 9(1), 19-29.
  32. Liang, D., Lu, C. C., Tsai, C. F., & Shih, G. A. (2016). Financial Ratios And Corporate Governance Indicators In bankruptcy Prediction: A Comprehensive Study. European Journal of Operational Research, 252(2), 561– 572. https://doi.org/10.1016/j.ejor.2016.01.012
  33. Lind, D. A., Marchal, W. G., & Wathen, S. A. (2019). Basic Statistics for Business & Economics (Ninth Edit). McGraw-Hill Education.
  34. Mahaningrum, A. A. I. A., & Merkusiwati, N. K. L. A. (2018). Pengaruh Rasio Keuangan pada Financial Distress.
  35. E-Jurnal Akuntansi, 30(8), 1969–1984. https://doi.org/10.24843/EJA.2020.v30.i08.p06
  36. Mai, F., Tian, S., Lee, C., & Ma, L. (2018). Deep learning models for bankruptcy prediction using textual disclosures. European Journal of Operational Research, 274(2), 743–758. https://doi.org/10.1016/j.ejor.2018.10.024
  37. Moch, R., Prihatni, R., & Buchdadi, A. D. (2019). The effect of liquidity, profitability and solvability to the financial distress of manucatured companies listed on the Indonesia stock exchange (IDX) period of year 2015-2017. Academy of Accounting and Financial Studies Journal, 23(6), 1–16.
  38. Modigliani, F., & Miller, M. H. (1958). The Cost of Capital, Corporation Finance and the Theory of Investment: Reply. The American Economic Review, 55(3), 524–527.
  39. Modigliani, F., & Miller, M. H. (1963). Corporate Income Taxes and the Cost of Capital: A Correction. The American Economic Review, 53(3), 433–443.
  40. Mousavi, M. M., Ouenniche, J., & Xu, B. (2015). Performance Evaluation Of Bankruptcy Prediction Models: An Orientation-Free Super-Efficiency DEA-Based Framework. International Review of Financial Analysis, 42, 64–75. https://doi.org/10.1016/j.irfa.2015.01.006
  41. Mselmi, N., Lahiani, A., & Hamza, T. (2017). Financial distress prediction: The case of French small and medium- sized firms. International Review of Financial Analysis, 50, 67–80. https://doi.org/10.1016/j.irfa.2017.02.004
  42. Nirmalasari, L. (2016). Analisis Financial Distress pada Perusahaan Sektor Property, Real Estate dan Konstruksi Bangunan yang Terdaftar di Bursa Efek Indonesia. Jurnal Manajemen Bisnis Indonesia (JMBI), 1, 46–61.
  43. Nurfajrina, A., Siregar, H., & Saptono, I. T. (2016). Financial distress. 20(3), 448–457.
  44. Ogachi, D., Ndege, R., Gaturu, P., & Zoltan, Z. (2020). Corporate Bankruptcy Prediction Model, a Special Focus on Listed Companies in Kenya. Journal of Risk and Financial Management, 13(3), 47. https://doi.org/10.3390/jrfm13030047
  45. Opitalia, M., & Zulman, M. (2019). Determinan Financial Distress pada Perusahaan Sektor Property di Bursa Efek Indonesia. Jurnal Riset Ekonomi Dan Bisnis, 12(3), 167–179.
  46. Oz, I. O., & Simga-Mugan, C. (2018). Bankruptcy Prediction Models’ Generalizability: Evidence From Emerging Market Economies. Advances in Accounting, 41(February), 114–125. https://doi.org/10.1016/j.adiac.2018.02.002
  47. Paule-Vianez, J., Gutiérrez-Fernández, M., & Coca-Pérez, J. L. (2019). Prediction of financial distress in the Spanish banking system. Applied Economic Analysis, 28(82), 69–87. https://doi.org/10.1108/aea-10-2019- 0039
  48. Pham Vo Ninh, B., Do Thanh, T., & Vo Hong, D. (2018). Financial Distress And Bankruptcy Prediction: An Appropriate Model For Listed Firms In Vietnam. Economic Systems, 42(4), 616–624. https://doi.org/10.1016/j.ecosys.2018.05.002
  49. Pradana, R. S. (2020). Analisis Financial Distress pada Perusahaan Pertambangan Batu Bara yang terdaftar di Bursa Efek Indonesia periode 2017-2018. Jurnal Akuntansi Dan Bisnis: Jurnal Program Studi Akuntansi, 6(1), 36–45. https://doi.org/10.31289/jab.v6i1.2825
  50. Ross, S. A., Westerfield, R. W., Jaffe, J., & Jordan, B. D. (2013). Corporate Finance (Tenth Edit). McGraw-Hill Education.
  51. Safitri, E., & Fitantina. (2016). Analisis Prediksi Kebangkrutan Pada Perusahaan Perbankan Go Public Di Bursa Efek Indonesia. Jurnal Ilmiah STIE MDP, 6(1), 16–28.
  52. Sekaran, U., & Bougie, R. (2016). International Standard Classification of Occupations (ISCO). In Encyclopedia of Quality of Life and Well-Being Research (Seventh Ed). John Wiley and Sons. https://doi.org/10.1007/978- 94-007-0753-5_102084
  53. Selvytania, A., & Rusliati, E. (2019). UKURAN PERUSAHAAN DAN GOOD CORPORATE GOVERNANCE
  54. TERHADAP TERJADINYA KONDISI FINANCIAL DISTRESS. Jurnal Riset Bisnis Dan Manajemen, 12(2), 70–76.
  55. Shahwan, T. M. (2015). The Effects of Corporate Governance on Financial Performance and Financial Distress: Evidence from Egypt. Historia de La Nación y Del Nacionalismo Español, 15(5), 543–562. https://doi.org/http://dx.doi.org/10.1108/CG-11-2014-0140
  56. Shen, F., Liu, Y., Wang, R., & Zhou, W. (2020). A dynamic financial distress forecast model with multiple forecast results under unbalanced data environment. Knowledge-Based Systems, 192. https://doi.org/10.1016/j.knosys.2019.105365
  57. Shrivastava, A., Kumar, K., & Kumar, N. (2018). Business distress prediction using bayesian logistic model for Indian firms. Risks, 6(4). https://doi.org/10.3390/risks6040113
  58. Svabova, L., & Michalkova, L. (2020). The impact of Data structure on classification ability of financial failure prediction model. SHS Web of Conferences, 74. https://doi.org/10.1051/shsconf/20207405024
  59. Tirto.id. (2020). Mereka yang Untung dan Buntung Tatkala Pandemi COVID-19. https://tirto.id/mereka-yang- untung-dan-buntung-tatkala-pandemi-covid-19-eL5l.
  60. Tobback, E., Bellotti, T., Moeyersoms, J., Stankova, M., & Martens, D. (2017). Bankruptcy prediction for SMEs using relational data. Decision Support Systems, 102, 69–81. https://doi.org/10.1016/j.dss.2017.07.004
  61. Veganzones, D., & Severin, E. (2020). Corporate failure prediction models in the twenty-first century: a review. European Business Review. https://doi.org/10.1108/EBR-12-2018-0209
  62. Yadiati, W. (2017). The Influence Of Profitability On Financial Distress: A Research On Agricultural Companies Listed In Indonesia Stock Exchange. Journal of Scientific & Technology Research, 6(11), 233–237.
  63. Yazdanfar, D., & Öhman, P. (2020). Financial Distress Determinants Among SMEs: Empirical Evidence From Sweden. Journal of Economic Studies, 47(3), 547–560. https://doi.org/10.1108/JES-01-2019-0030