Kavita Kavita
Universitas Prima Indonesia

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Ketepatan Altman Score, Zmijewski Score, Grover Score, dan Fulmer Score dalam menentukan Financial Distress pada Perusahaan Trade and Service Munawarah Munawarah; Anton Wijaya; Cindy Fransisca; Felicia Felicia; Kavita Kavita
Owner : Riset dan Jurnal Akuntansi Vol. 3 No. 2 (2019): Owner Volume 3 Nomor 2 Agustus 2019
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (601.238 KB) | DOI: 10.33395/owner.v3i2.170

Abstract

This research purpose to determine the accuracy among Altman, Zmijewski, Grover, and the Fulmer models in predicting financial distress, and to determine the most accurate prediction models to use in Trade and Service company. With the accuracy of the overall prediction model of 89.4%, this research will compare the four prediction models using real conditions of the company. The Data that used in this research are all form of annual financial reports published by companies on the Indonesia Stock Exchange website. The population used is Trade and Service’s company listed on the Indonesia Stock Exchange for the period 2013-2017. Purposive sampling used in this research to obtain 34 companies as research sample. This research compares four prediction models of financial distress using logistic regression analysis. According to the result of this research shows the accuracy between the Altman, Zmijewski, Grover, and Fulmer models to predict financial distress, which the highest level of accuracy is achieved by Zmijewski model and Fulmer model with a value of 100%, followed by Grover model with a value of 97% while Altman model with a value of 73,5%.