Analisis Financial Distress Dengan Model Altman, Grover, Springate, Zmijewski, dan Ohlson Pada Perusahaan Jasa Konsumen Yang Terdaftar Di BEI

Precision Of The Model Of Altman, Grover, Springate, Zmijewski, and Ohlson For Predicting Financial Distress In Consumer Services Subsector Companies Listed On IDX

Studi ini bertujuan untuk mengetahui “adanya perbedaan diantara model analisis Altman, Grover, Springate, Zmijewski, dan Ohlson serta tingkat akurasi dan tipe error tiap model guna memprediksi financial distress pada perusahaan subsektor Jasa Konsumen yang terdaftar di BEI periode 2016-2020.” Penentuan sampel di studi ini menggunakan metode “purposive sampling”. Jumlah sampel penelitian ini yaitu sebanyak 20 perusahaan subsektor Jasa Konsumen. Teknik analisis data yang dipakai yakni lewat hitung score tiap model, uji analisis deskriptif, uji normalitas, uji paired sample t-test, dan uji tingkat akurasi serta tipe error yang membandingkan dengan kondisi nyata perusahaan. Hasil studi ini menyimpulkan jika terdapat perbedaan yang signifikan diantara kelima model analisis guna prediksikan “financial distress”. Hasil uji tingkat akurasi menunjukkan jika model analisis dengan tingkat akurasi tertinggi yaitu model Grover sebesar 82%, model Zmijewski 80%, model Altman 77%, model Springate 48%, dan model Ohlson 24%. Kesimpulan dari penelitian ini yaitu model Grover menjadi model terbaik untuk prediksikan “financial distress” di perusahaan subsektor Jasa Konsumen yang terdata di BEI periode 2016-2020.

The goal of this research is to determine the differences between the Altman, Grover, Springate, Zmijewski, and Ohlson analysis models, as well as the level of accuracy and error type of each model in predicting the financial distress of consumer services subsector companies listed on the IDX from 2016 to 2020. Sample determination in this study using purposive sampling methods. The number of samples of this study is as many as 20 consumer services subsector companies. The data analysis techniques used are by calculating the score of each model, descriptif analysis test, normality test, paired sample t-test, test accuracy rate and error type that compares with the company's real condition. The results of this study showed that there is a significant difference between the five analytical models in predicting financial distress. The results of the accuracy rate test showed that the analysis model with the highest accuracy rate was the Grover model at 82%, the Zmijewski model at 80%, the Altman model at 77%, the Springate model at 48%, and the Ohlson model at 24%. So it can be concluded that the Grover model is the most suitable model for predicting financial distress in Consumer Services subsector companies listed on the IDX from 2016 to 2020.