PREDICTING CORPORATE BANKRUPTCY: BASED ON MDA TEXTILE AND GARMENT ON INDONESIA STOCK EXCHANGE - Afgani, Kurnia Fajar; Rivanda, Agil Krisna; Purbayati, Radia (2021)
During the Covid-19 Pandemic, Indonesian companies, especially the various industrial sectors, were affected in various ways. This may have an impact especially in the textile and garment sub-sector, while one of the strategic sectors that continue to make a significant contribution to the national economy, such as exports of non-oil foreign exchange earner, employment, and domestic needs. It is therefore important to know the company's bankruptcy to do with predicting bankruptcy. This study uses a statistical model of multiple discriminant analysis (MDA). This is a model developed by Altman in a study to predict the failure of a company.The statistical method used is discriminant analysis using five Altman variables, namely working capital/total assets, retained earnings/total assets, earnings before interest/total assets, and taxes, market value equity to book value of total debt and sales to total assets. There are 17 textile and garment companies available on the Indonesia Stock Exchange for the period 2015 to 2020. The results also show that the five independent variables used are significant in distinguishing between the bankruptcy prediction group and the non-bankruptcy prediction group through the F test and the Wilks Lambda test. At < 0.05, the ratio of WC/TA and EBIT/TA is the most dominant independent variable in distinguishing between groups that are predicted to be bankrupt and not bankrupt