This research aims to predict financial distress in property and real estate sector companies, before and during the pandemic of Covid-19 using the Altman Z'-Score and Sprigate S-Score ratio analysis. The population of this research is all property and real estate companies listed on the Indonesian Stock Exchange for the period 2018 to 2020, so the population of this study is 66 companies. The sample was selected based on predetermined purposive sampling criteria. Those selected according to the specified sample criteria were 44 companies. The data analysis technique used the Altman Z-Score and Springate S-Score discriminant analysis techniques. The results of this study indicate an increase in the number of companies in the distressed category (red zone) during the COVID-19 pandemic (in 2020) by 16%, which was twice as high as before the Covid-19 pandemic, which was 7%. This indicates that there are difficulties both financially and in liquidity as well as a decrease in the company's ability to grow, which may lead to bankruptcy.
The profit growth of manufacturing companies in the food and beverage sector is expected to experience obstacles. This could be due to the decline in the Islamic capital market. while the performance of management will be reflected in the profits to be generated by the company. There are several obstacles faced by the company in the process of generating maximum profit, such as intense competition between sectors, decreasing people's purchasing power. The purpose of this study was to determine the effect of financial ratios on profit growth moderated by economic growth. The research method used in this study is a quantitative method with a descriptive statistical approach. The population used in this study are food and beverage manufacturing companies listed on the stock exchange with a total of 45 companies, while the sample is 11 companies. The data analysis used in this research is panel data regression analysis using classical assumption test, hypothesis testing, and moderated regression analysis. The result of the research is that the financial ratios proxied by NPM, CR and TATO have an effect on changes in profits, either simultaneously or partially. This means, an increase or decrease in the value of NPM, CR and TATO will have an impact on the increase or decrease in the value of changes in profit, and economic growth has a direct effect on changes in profits.
Kinerja perusahaan tergantung dari operasional perusahaan dan kinerja perusahaan dapat dilihat melalui laporan keuangan. Laporan keuangan dapat dijadikan alat ukur untuk menganalisis kinerja perusahaan tersebut baik atau tidak. Penelitian ini bertujuan untuk mengetahui kinerja keuangan perusahaan sub sektor cosmetic and household di Indonesia yang terdaftar di Bursa Efek Indonesia Tahun 2015 – 2019 dengan pendekatan Du Pont System secara Time Series Approach (TSA) dan Cross Sectional Approach (CSA). Analisis ini bersifat lebih menyeluruh dan dapat mengetahui seberapa kuat hubugan penggunaan hutang, perputaran aktiva, marjin laba serta ROI terhadap ROE. Penelitian ini merupakan penelitian deskriptif kuantitatif. Hasil penelitian ini menunjukkan analisis Return On Investment (ROI) dan Return On Equity (ROE) dengan Time Series Approach (TSA) pada Tahun 2015 sampai dengan 2019 mengalami penurunan dan fluktuatif. Analisis Du Pont System secara Cross Sectional Approach (CSA) pada industri perusahaan sub sektor cosmetic and household di Indonesia sebesar 3.428%. Hal ini menunjukkan bahwa secara keseluruhan dikatakan perusahaan sub sektor cosmetic and household berkinerja BAIK.
This study aims to financial distress predict and the level of accuracy using the Springate model in the property and real estate sector listed on the Indonesia Stock Exchange for the 2019-2020 period. The population of this study is all property and real estate companies listed on the Indonesia Stock Exchange for the 2019-2020 period, so the population of this study managed to find 66 companies. Samples were selected based on predetermined purposive sampling criteria. The sample selected according to the specified criteria is 37 companies. The data analysis technique used the Springate S-Score discriminant analysis technique. The results of the bankruptcy analysis using the Springate method, namely in 2019 before the onset of covid-19 there were 27 property and real estate companies in financial distress and 10 companies in healthy condition (non-financial distress). In 2020, during the COVID-19 pandemic, there were additional companies that were in financial distress, namely 34 companies and only 3 companies that remained in a healthy condition (non-financial distress). Based on the results of the analysis of the Springate method in predicting bankruptcy in property and real estate sector companies, it has an accuracy rate of 62.2%.
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