Menakar Tingkat Keakuratan Prediksi Financial Distress melalui Tiga Model Prediksi Pada Industri Otomotif

Rini Ridhawati (Universitas Mataram, Indonesia)
Adhitya Bayu Suryantara (Universitas Mataram, Indonesia)

Valid Jurnal Ilmiah
Vol. 20 No. 2 (2023)

The automotive industry is one of the mainstay sectors in spurring national economic growth. Indonesia has the second-largest car manufacturing industry in the ASEAN region. However, based on data from the combined car and motorcycle tool industry (GIAMM), in 2018, the export value was lower than the import value of automotive components, resulting in a deficit of hundreds of millions of US dollars. This condition allows companies to experience financial distress due to decreased company productivity. This study aims to compare the financial distress prediction model in the automotive industry listed on the Indonesia Stock Exchange using the Altman, Grover, and Springgate models. The results of this study indicate that the Altman model is the most accurate predictor of financial distress, with an accuracy rate of 87%, followed by the Grover model with 84% and the Springate model with 80%.