ANALYSIS FINANCIAL PERFORMANCE USING ALTMAN (Z-SCORE) DISCRIMINANT MODEL TO CALCULATE THE RISK OF COMPANIES GOING BANKRUPT IN MANUFACTURING INDUSTRY INDONESIA

• Main Author: Diandra, Muhamad
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/81227
• Institution: Institut Teknologi Bandung

Altman (Z-Score) model is one of multivariate analysis model that can be used to predict company bankruptcy with the level of exactness and accuracy that can be trusted relatively. The objective of this research is to know the prediction of bankruptcy and financial performance of the companies based on discriminant analysis result by using Altman model. Beside is to know the risk management in order to manage companies that tend to bankrupt. The research samples are 30 companies of manufacturing industry which are listed in Indonesia Stock Exchange. This manufacturing industry consists of numerous sectors including automotive sector, textile & garment, cable & electronic, and footwear. Research data that has been collected is secondary data with the period 2005-2008. Data resource of this research has taken from financial statement of companies which can be found in Bloomberg, Bank Indonesia. Analysis data technique that used by researcher is discriminant analysis model of Altman which recognizable as Z-Score prediction model. The result of this research showed that 80 percent of companies were in the bankrupt condition with different level of bankruptcy in each sector. Based on the analysis that has done the worst level of bankruptcy sector is textile & garment sector. Good condition of financial statement in the company reflect the good financial performance, conversely bad condition of financial statement reflect the bad financial performance. The dominant factors that affect Z-Score value are market value of equity, retained earnings, and working capital. Altman prediction model can be used to assist investors, creditors, and regulators in Indonesia and other emerging economies to predict corporate failure.