Studi Pengelompokan Perbankan berbasis fuzzy c-mean dan fuzzy gustafson kessel

  • Kartika Ayu Kinanti University of Jember
  • Hari Sukarno University of Jember
  • Elok Sri Utami Universitas Jember
Keywords: Fuzzy C-Means, Fuzzy Gustafson Kessel, Banking.

Abstract

The banking sector as one of the drivers of the economy plays an important role in society. Over time, bank operations are not only collecting funds from the public but are more complex. The development of the banking industry can be seen from the number of banks in Indonesia that spur the level of competition. Of course, banks must pay attention to their health. The use of bank soundness or RGEC parameters combined with clusters is interesting to study. By using the cluster method, banks can be classified based on the parameters of their soundness level. This study aims
to analyze the classification of bank groupings based on RGEC generated by clustering analysis of the Fuzzy C-Means and Fuzzy Gustafson Kessel methods using financial ratio data on 80 conventional banks in Indonesia. The software used in this research is Matlab r2015b. The results showed that the Clustering FCM had a smaller standard deviation than the FGK so that cluster 1 in the FCM showed that the bank was in good condition compared to the other clusters, although the overall condition of Banks in Indonesia was good when viewed from their financial performance

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Published
2021-09-19