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Financial distress is a condition whene the company are in a state financial difficultes. Every company must have an early an early warning system to detect the potential for financial distress in order to avoid bankruptcky. The Purpose of this is to analyze and provide empirical evidence regarding the effect profitability (ROA), as a moderating between liquidity (CR), leverage (DAR), sales gowth (SG), in predicting financial distress (Altman Z-Score). The population in this purpose were retail companies on the IDX for the 2016-2020 period, with a sample of 19 companies studied for 5 years so that 95 samples were obtained, using the purposive sampling method. The data used is secondary data in the form of information from the company’s financial statements. The data analysis technique used logistic regression and moderating regretion analysis (MRA). The rsults prove that the variables of liquidity, sales growth and profitability are able to predict financial distress, while leverage cannot predict financial distress, the profitability variable strengthens the influence of liquidity and sales growth in predicting financial distress but weakens leverage in predicting financial distress. The advince given is expected thet the company can increase the effectiveness and efficiency in managing assets and can increase sales so that the profit received by the company increases so that the company can avoid financial distress.

Penelitian ini dilakukan untuk mengetahui kemungkinan terjadinya financial distress pada perusahaan sub sektor transportasi akibat dari adanya dampak pandemic covid-19 pada periode 2020 dengan menggunakan metode Altman Z-Score. Data yang digunakan pada penelitian ini adalah laporan keuangan perusahaan sub sektor transportasi periode 2020 yang diperoleh dari Bursa Efek Indonesia. Penilaian financial distress menggunakan rumus Z-Score Modifikasi atau Model III yang dikemukakan oleh Altman dengan menggunakan 3 kategori kalsifikasi yaitu kategori sehat, rawan atau grey area, dan financial distress. Hasil dari penelitian ini menunjukkan bahwa terdapat 13 perusahaan yang mengalami financial distress, 5 perusahaan berada pada kondisi rawan atau grey area, serta 5 perusahaan yang berada pada kondisi sehat. Variabel-variabel yang digunakan sangat berpengaruh pada hasil perhitungan analisis Altman Z-Score, terutama apabila perusahaan mengalami defisiensi modal maka kemungkinan terjadinya financial distress pada perusahaan juga semakin tinggi.

This study aims to determine the difference in results in predicting bankruptcy using the Altman Z-Score model and the Springate S-Score model, as well as ineasures which model is most accurate in predicting bankruptcy at retail companies at Indonesia. The population used in this study are retail companies listed on the Indonesia Stock Exchange (IDX) for the 2016-2020 period with a sample of 11 companies. The sampling method used in this study was purposive sampling. The data analysis technique used multiple discriminant analysis. The results showed that there were differences in the results in predicting bankruptcy before and during the pandemic. Based on the two measurement methods used, before the pandemic there were 4 companies that were declared bankrupt and 7 companies that were declared healthy. During the pandemic, 8 companies were declared bankrupt and 3 companies were declared healthy. The bankruptcy model that has the highest level of accuracy is the Springate S-Score.

Based on the data obtained, this study was made with the intention of analyzing and examining the liquidity andleverage variables in financial distress with the profitability ratio as moderating in manufacturing companies listed onthe IDX with 3 years of observation, namely the 2017-2019 period. The independent variable is proxied by usingCurrent Ratio (CR) as the liquidity variable and Debt to Equity Ratio (DER) as the leverage variable. The moderatingvariable is proxied using Return on Assets (ROA), while the variable using the Z-Score proxy (Altman). The populationis manufacturing companies for the period 2017-2019 and is listed on the IDX. The sample taken is 99 manufacturingcompanies with purposive sampling method. The method of analysis uses logistic regression. The results of the researchtested show that CR has an effect on financial distress. Meanwhile DER does not affect financial difficulties. However,it is different from ROA, ROA, the effect of CR and DER on financial distress.