Artificial Neural Network and Fuzzy Neural Network Algorithm for Financial Health Analysis of Indonesian SOEs

Abstract

The determining of financial soundness of SOEs company is regulated by the government through Decree of the Minister of SOEs KEP: 100 / BUMN / 2002. There are 8 parameters to be calculated for determining financial soundness such as ROE, ROI, cash ratio, current ratio, collection periods, inventory turnover, TATO, and ratio of total equity to total assets. From the calculation results based on these rules, there are 3 categories of companies, that is healthy, less healthy and unhealthy. To calculate the best parameters as a significant aspect to determining financial soundness, this research using neural networks method. In this paper, it compares the value of accuracy and learning rate with Artificial Neural Network and Fuzzy Neural Network method. Accuracy used as the fitness value of the Genetic Algorithm, to get the top three parameters from eight parameters to determining the financial soundness of SOEs companies. The result of this research both ANN and FNN get the same top three parameters: ROE, ROI, and Cash Ratio. In overall, artificial neural network or fuzzy neural network algorithm both suitable for use in the financial health analysis of SOEs companies.