AN ISLAMIC BANK RISK ANALYSIS BASED ON ITS BALANCE SHEET

This study aims to see the performance of an Islamic bank and analyze the risks that may be impact by an Islamic bank using the Economic Value Added (EVA) method. The data taken from the directory of each bank and the website of the Otoritas Jasa Keuangan (OJK). The selected bank criteria are gov...

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Bibliographic Details
Main Author: Resta Gusnia, Welni
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/60930
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:This study aims to see the performance of an Islamic bank and analyze the risks that may be impact by an Islamic bank using the Economic Value Added (EVA) method. The data taken from the directory of each bank and the website of the Otoritas Jasa Keuangan (OJK). The selected bank criteria are government-owned banks in this study using BNI Syariah bank data, with data taken from the last 10 years,from 2011 to 2020, with a total of 40 data series. This study uses three analytical models to see the forecasting results compared with the validation data for the II, III, and IV quarters in 2020, they are ARIMA model,intervention analysis model and the causal impact model. Furthermore, the author will look at the factors that influence the risk of an Islamic bank, and how that risk has an impact on the economic value added of a bank. The test tool that used in this study is forecasting EVA data using the time series , intervention time series and causal impact package R. The results of this study showed that of the three models for predicting the effect of the pandemic on EVA, the best model obtained was the time series model with intervention with a percentage error of validation data with forecasting data after the intervention is 11%, while the ARIMA model is 99%, and the causal impact model concludes that the intervention effect is not statistically significant because the time period after the intervention is too short. Islamic bank risks, they are credit and operational risk, cash adequacy ratio using multiple linear regression to show its correlation to EVA using T-test and F-Test conclude that credit and operational risks have an influence on EVA