Analisis Prediksi Financial Distress Dengan Menggunakan Metode Altman Z – Score Pada Industri Pertambangan Minyak Dan Gas Bumi Yang Terdaftar Di Bursa Efek Indonesia Periode 2013-2017

Meci Zahara

Abstract


The Background of this research is to know and to analize prediction of company bankruptcy of mining Industry in BEI periods 2013-2017. which focuses object are three companies which have all criteria in analysis by method Z-score Altman. As we know, the goal of company is not being bankrupt so that the company needed a method to predict the bankruptcy as soon as possible. One of the method is Z-Score Altman, this method used to analize financial statements. The Altman model (Z score) is one of the multivariate analysis models that is useful for predicting corporate financial distress with a reliable level of accuracy. This study aims to determine the analysis of financial distress and also the company's financial performance based on discriminant analysis using the Altman Model. The research data collected is secondary data in the period 2013-2017. While the data source of this study was collected from the company's financial reporting in the Indonesian Capital Market Directory (ICMD). Data analysis - the technique we use is the Altman discriminant analysis model known as the Z score prediction model. The company used as the object is company bankruptcy of mining Industry analyzed using financial statements taken from 2013 to 2017. After that the working capital to total assets (X1), retained earnings to total assets (X2), earnings before interest and taxes to total assets (X3), market values equity to the book value of total debt (X4) and sales to total assets (X5) then calculated the value of each variable into Altman's Formula to produce a score (Z-Score). Determine the Z-Score in this category: a) Z-Score < 1,81 are on potential bankruptcy category; b) 1,81 < Z-Score < 2,99 are on grey area category; c) Z-Score > 2,99 are on non bankruptcy company. The results of this study show the fact that all companies in the Mining Industry Stones and Mineral metals are bankrupt and Rock-prone with Z-level scores - Different scores.


Keywords


Financial Distress., Method of Altman Z-Score

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DOI: http://dx.doi.org/10.33087/sms.v1i10.47

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