ANALISIS AKURASI MODEL – MODEL PREDIKSI FINANCIAL DISTRESS

(Studi empiris pada perusahaan yang termasuk dalam Kantar’s 2019 Top 30 Global Retails (EUR))

ACCURACY ANALYSIS OF FINANCIAL DISTRESS PREDICTION MODEL

 (Empirical Study on Companies included in Kantar 2019 Top 30 Global Retails (EUR))

Penelitian ini bertujuan untuk menemukan model prediktor financial distress yang paling akurat. Perusahaan berpotensi bangkrut. Kebangkrutan dapat diprediksi dengan menggunakan model yang akurat sebagai peringatan dini untuk mengantisipasi financial distress. Penelitian ini dilakukan pada industri ritel global yang termasuk dalam Kantar's 2019 Top 30 Global Retails (EUR). Data dalam penelitian ini diambil dari 60 laporan tahunan periode 2018-2019 dan sampel 30 perusahaan ritel global. Tingkat akurasi dihitung dengan jumlah prediksi yang benar dibagi dengan total data dan dikalikan dengan seratus persen. Penelitian ini membandingkan empat model prediktor financial distress, yaitu model Altman, model Springate, model Taffler, dan model Grover. Dengan hasil penelitian, model Grover memiliki tingkat akurasi tertinggi, yaitu 76,67%.

Kata kunci : Model Atlman; Kesulitan Keuangan; Model Grover; Model Springate; Model Taffler.

This study aims to find the most accurate predictor model of financial distress. The company has the potential to go bankrupt. Bankruptcy can be predicted using an accurate model as an early warning to anticipate financial distress. This research was conducted on the global retail industry which is included in Kantar's 2019 Top 30 Global Retails (EUR). The data in this study were taken from 60 annual reports for the 2018-2019 period and a sample of 30 on global retail companies. The accuracy rate is calculated by the number of correct predictions divided by the total data and multiplied by one hundred percent. This study compares four predictor models of financial distress, namely the Altman model, the Springate model, the Taffler model, and the Grover model. With the results of the study, the Grover model has the highest level of accuracy, which is 76.67%.

Keywords : atlman model; financial distress; grover model; springate model; taffler model.