Prediction Analysis of Company Bangkruptcy Using Comparison of the Altman Method (Z-score) and Grover Method (G-scrore) as an Early Warning System in Pharmaceutical Subsector Companies

Abstract

Pharmaceutical companies are part of the manufacturing sub-sector of the health sector, at the end of 2019 the outbreak of the Covid-19 virus weakened the country's economic sector, so this was also felt by pharmaceutical companies. The outbreak of the Covid-19 virus has created high market demand for medicines and medical devices, this has increased raw materials because 90% of pharmaceutical raw materials in Indonesia are still imported, as a result, if company management does not act immediately, this will lead to bankruptcy. The research objective is to predict the bankruptcy of pharmaceutical companies listed on the Indonesia Stock Exchange in 2019-2021 by using a comparison of the Altman method (Z-Score) and the Grover method (G-Score). Using a type of quantitative research using secondary data from the annual financial reports of pharmaceutical companies listed on the Indonesia Stock Exchange for 2019-2021. The data collection technique uses a saturated sample technique using data analysis, namely the Altman method (Z-Score) and the Grover method (G-Score). The results show that from the annual calculations using the Altman method, there are 6 companies in healthy condition and 3 companies in distress and gray areas, while the Grover method calculates that all companies, namely 9 companies, are declared to be in financially healthy condition with 27 samples of data for 2019-2021. In calculating the level of accuracy, the Altman method obtains an accuracy of 77.7%, while the Grover method obtains an accuracy of 100% by looking at the number of correct predictions and the entire sample.