Analisis Tingkat Kesehatan Bank Syariah di Indonesia Menggunakan Metode Fuzzy Inference System Takagi-Sugeno-Kang

Abstract

This study aims to measure the level of accuracy of the health of Islamic banks in Indonesia using the RGEC (Risk Profile, Good Corporate Governance, Earning, and Capital) method and the Takagi-Sugeno-Kang (TSK) Fuzzy Inference System. Fuzzy Inference System is an Artificial Intelligence method that can measure the level of accuracy well. The application of the Takagi-Sugeno-Kang Fuzzy Inference System in assessing the health level of 12 Islamic banks in Indonesia begins by dividing the data into 40 data for training and 20 for testing. The inputs used are NPL, LDR, ROA, ROE, NIM and CAR. The level of accuracy obtained in the fuzzy system for training data for 2014, 2015, 2016, 2017 and 2018 is 95.4%, 97.7%, 98.2%, 96.8%, and 95.4%. In the testing data, the accuracy value for 2014, 2015, 2016, 2017 and 2018 is 100%.