GOING CONCERN ESTIMATION BANKING INDUSTRY IN INDONESIA WITH ADAPTIVE NEURO FUZZY INFERENCE SYSTEM APPROACH (USING IPSA 30.2) - Mailda Alfriska (Universitas Gunadarma, 2017)
The growing activities of the economy the way it is today. The users of the financial statements, in which case it is investors sometimes cannot understand the meaning contained in the financial statements the company made. Investors will be easier to read and more trust financial statements audited . This research aims to observe granting the assumption of going concern (variable output) so it could be assessed by observe the five variables that are used by the auditor in granting the assumption of going concern an enterprise that is CAR, LDR, ROA, net income growth and the Z-Score (input variables). The population of this research is a banking company listed on the Indonesia stock exchange period 2007-2011. The Total sample of the research is 15 company that determined throught purpose sampling. Analysis tools used is adaptive neuro fuzzy inference system. Adaptive neuro fuzzy inference system approach is a blend of artificial neural network and fuzzy logic. Overall analysis and preparation is done with the help of variable Matlab R2010b. Based on the analysis that was done, fuzzy system generates 6 fuzzy rules can define input-output behavior. The results of this research indicates the level of accuracy is quite high with an average error rate is able to achieve 0 i.e. 0,1820 afterwards in test with sample 4 banking company which are Bank Pan Indonesia period 2008-2011, Bank Permata, Bank Rakyat Indonesia and Bank Victoria International in the period 2007-2011. Keywords: Adaptive Neuro Fuzzy Inference System, Fuzzy, Going Concern Assumption