Aplikasi Altman’s Z-Score untuk Memprediksi Kepailitan pada Perusahaan yang Terdaftar di Bursa Efek Indonesia Tahun 2008-2017

Anindyajati, Andreas Anggara (2018) Aplikasi Altman’s Z-Score untuk Memprediksi Kepailitan pada Perusahaan yang Terdaftar di Bursa Efek Indonesia Tahun 2008-2017. Bachelor Thesis thesis, Universitas Multimedia Nusantara.

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Abstract

Altman’s Z-Score is a matematical model consists four to five financial variabels that can be used by investor and company’s management to predict company’s bankruptcy. This study aims to find out how accurate the Altman Z”- Score in predicting bankruptcy of a company in Indonesia in the period 2008 until 2017. The result is Altman’s Z”-Score prediction is able to reach 75% with the total population of 32. The population in this research is divided into two groups, the first group is companyies that go bankrupt and delisted from the Indonesia Stock Exchange named “class A”, the second group consist companies that are still listed in Exchange is named “class B”. A total of eight bankrupt companies are incorporated in class A, and class B becomes a control sample for class A that contains companies with similar charatecristics. This research found that are some variables of Altman’s Z”-Score that can be used as early signs of company’s bankruptcy, that has negative values of retained earnings, can not produce a positive EBIT, and have debt quite high. The author hopes the result of this study can be useful for investor to save their investment and company’s management in order to save the company and avoid bankruptcy.

Item Type:	Thesis (Bachelor Thesis)
Subjects:	300 Social Sciences > 330 Economics > 332 Financial Economics (Shares, Investment) > 332.6 Investment 300 Social Sciences > 330 Economics > 336 Public Finance 600 Technology (Applied Sciences) > 650 Management and Public Relations > 658 General management (Risk Management, Profit and Loss, Logistics) > 658.7 Management of Supplies, Stock
Divisions:	Faculty of Business > Management
Depositing User:	Administrator UMN Library
Date Deposited:	13 May 2019 01:39
Last Modified:	11 Apr 2023 00:51
URI:	https://kc.umn.ac.id/id/eprint/5662

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