Analysis of Financial Distress in Measuring Bankruptcy Before and After The Covid-19 Pandemic - Supitriyani Supitriyani; Yansen Siahaan; Astuti Astuti; Juan Anastasia Putri; Elly Susanti (Journal of Governance Risk Management Compliance and Sustainability, 2021)
The increasing spread of the Covid-19 virus at this time has forced several company sectors to experience setbacks in their operations. This epidemic has had a major impact, especially on the Transportation Sub-Sector Companies because they have to make some adjustments to government regulations such as implementing health protocols and physical restrictions on travel to break the chain of virus spread. The regulation has an impact on the company's revenue decline and the potency to suffer losses that can result in bankruptcy. This study aims to determine the bankruptcy prediction of the Transportation Sub-Sector Companies listed on the IDX before and after the covid-19 pandemic and to find out the most accurate method. The sampling technique used was non-probability sampling with the purposive sampling technique. The method used is descriptive with a quantitative approach. The results of the hypothesis test show that there are differences in predictions between the Altman and Springate models in predicting bankruptcy before and after the covid-19 pandemic. The Altman model is the most accurate prediction with an accuracy rate of 85.75%, while the Springate model has an accuracy rate of 73%. The study focused on companies listed on the IDX and used two bankruptcy measurement models, so researchers are next expected to use the entire company and other existing bankruptcy prediction, models. In addition, some factors beyond the control of researchers, such as economic conditions that cannot be measured. The renewal of previous research is to use two methods of prediction of bankruptcy, different objects, and research time (before and after the covid-19 pandemic).