<![CDATA[ABSTRACT Purpose -The purpose is developing early warning system (EWS) model for small Islamic financing (SMIF) or UMKM by artificial neural networks (ANNs) method as a tool can more usefull for mitigating risk in Islamic bank,(iB/BUS). Methodology – The analysis consists of three main steps. First step prediction analyzing list risk exposure which is commonly used by Islamic Bank SME product, especially at murobaha aqd by multyvariate regression method. Second is appearance significant risk for identifying as main variables by logistic regression. Third is the implementation of appropriate ANNs model design according to neural networks properties for evaluation based on simulated return predictions/classification of UMKM financing risk model. Originality – Value in this paper is scarcity theme in EWS development mitigate risk utilizing ANNs method esspecially for Indonesian islamic syaria bank case SME-UMKM. Findings – It is shown that situasional changes of risk exposure can be predicted and classified quite well. The model provides an alternative for early warning analyzing mitigate risk exposure. Found risk exposure is predicted cause cross reference of data. Practical Implications- Contribution ANN methodology usage of many variety islamic research bisnis model especially in credit risk granting at iB institution. Keywords-IslamicBanks,Risk,ANNs, SME,IB/BUS,EWS,CAMELS. Paper type Research paper ,thesis.]]>
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