Analisis Financial Distress Menggunakan Model Altman, Internal Growth Rate, dan Springate pada Perusahaan Subsektor Restoran, Hotel, dan Pariwisata yang Terdaftar di Bursa Efek Indonesia Tahun 2017-2021. (Financial Distress Analysis Using the Altman Model, Internal Growth Rate, and Springate in Restaurant, Hotel and Tourism subsector Companies Listed on the Indonesia Stock Exchange 2017-2021).

Cahyani, Ella Dwi (2023) Analisis Financial Distress Menggunakan Model Altman, Internal Growth Rate, dan Springate pada Perusahaan Subsektor Restoran, Hotel, dan Pariwisata yang Terdaftar di Bursa Efek Indonesia Tahun 2017-2021. (Financial Distress Analysis Using the Altman Model, Internal Growth Rate, and Springate in Restaurant, Hotel and Tourism subsector Companies Listed on the Indonesia Stock Exchange 2017-2021). Undergraduate thesis, Universitas 17 Agustus 1945 Surabaya.

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Abstract

At the end of 2019 to 2022 there is the phenomenon of the "Covid-19" pandemic which has a major impact on various areas of life. One of the areas affected by this phenomenon is the business in the restaurant, hotel and tourism sub-sectors. Many businesses in the sector have closed and many workers have been laid off. However, some are struggling to sustain business during the pandemic. The difficult times of the Covid-19 pandemic can also have an impact on increasing the risk of bankruptcy for surviving companies and increasing the difficulty of obtaining cash to pay off their obligations. Financial distress is the decline in the financial condition of the company and the difficulty of fulfilling obligations caused by a situation where the company's capabilities are weak. Financial difficulties are early signs of bankruptcy. So that this can be avoided early warning of bankruptcy can be obtained by conducting a bankruptcy analysis. The purpose of this study is to determine the potential for financial distress in companies in the restaurant, hotel and tourism sub-sector for the 2017-2021 period using the Altman model, internal growth rate, and Springate and to find out the most accurate model among the three models. Data analysis techniques using Altman model analysis, internal growth rate, and Springate, as well as testing the level of accuracy. The population used is the restaurant, hotel and tourism sub-sector companies listed on the IDX. Data collection techniques with the documentation method. Sampling using purposive sampling method. The type of data used is secondary data, namely in the form of financial report data published by the company every year. The data analysis method in this study uses quantitative descriptive analysis. The results of this study indicate that the Altman model can predict financial distress in hotel, restaurant and tourism subsector companies during the 2017-2021 period with an accuracy rate of 77.1% and a type error of 22.9%. The internal growth rate model can predict financial distress in these sub-sector companies with an accuracy rate of 70.5% and a type error of 29.5%. The Springate model can predict financial distress in these sub-sector companies with an accuracy rate of 14.3% and a type error of 85.7%. The most accurate model is the Altman model with the highest accuracy rate of 77.1% and a type error of 22.9%.

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