COMPARISON AND PREDICTING FINANCIAL PERFORMANCE OF ISLAMIC AND CONVENTIONAL BANKS IN INDONESIA TO ACHIEVE GROWTH SUSTAINABILITY
DOI:
https://doi.org/10.26740/al-uqud.v3n2.p174-187Keywords:
Islamic Banking, Financial Performance, Artificial Neural NetworkAbstract
Islamic banking fall on stagnation of financial performance in 2011 after successfully overcoming the financial crisis in 1998 and 2008, as though the Islamic banking sector had only run in place and had no clear purpose in developing the Islamic finance business. The purpose of this study is to clarify the variables that predispose financial performance, as well as predict the decrease and increase of financial performance. This study uses an Artificial Neural Network (ANN) model to find out the variables that affect financial performance and predict the decrease and increase of financial performance of sharia and conventional banking for the next five months. This research generates the variables which affect the financial performance of sharia banking and the prediction of financial performance over the next five months. The variables which affect the level of financial performance of sharia banking affected dominantly by inflation, although the results of conventional banking are the same but not too significant. This shows that sharia banking CBGB (Commercial Bank Group of Business) 2 is very vulnerable with macroeconomic factors compared with conventional banking. ANN predictions produce an average of 80% success in predicting performance over the next five months.
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