文章基本信息

标题：Neural Network Prediction Analysis: The Financial Distress Case
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作者：Rasyidi Faiz Akbar ; Musdholifah Musdholifah ; Purwohandoko Purwohandoko 等
期刊名称：Researchers World - Journal of Arts Science & Commerce
印刷版ISSN：2229-4686
电子版ISSN：2229-4686
出版年度：2018
卷号：9
期号：3
页码：119-125
DOI：10.18843/rwjasc/v9i3/15
出版社：Educational Research Multimedia & Publication
摘要：This study aims to to test internal financial factor company to financial distress in the year 2018 using data historical 2012-2018. The independent variable taken of a set the initial of du Jardin variables in 2010. Secondary data was used in the study with 32 mining firms that listed on the Indonesia Stock Exchange in 2012-2018 with purposive the sampling method of. A prediction done by means of a utensil artificial analysis the skill of artificial neural network. The application of a method of neural network used backpropagation algorithm. Architecture neural network used 3 layers (1 for input layer, 1 for hidden layer, 1 for output layer). The activation function used a logarithm sigmoid (logsig). The value of mean square error (MSE) training a network is 0,001. The results of forecasting neural network that there is no financial distress in 2018 with accuracy of prediction reaches 84,375%. For the next researcher, it is expected to use several models and several sectors as a comparison so that it can be proven which model is the most accurate in predicting symptoms of financial distress.