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Failure prediction of e-banking application system using adaptive neuro fuzzy inference system (ANFIS)

  • International Journal of Electrical and Computer Engineering (IJECE)
  • Institute of Advanced Engineering and Science (IAES)
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Problems often faced by IT operation unit is the difficulty in determining the cause of the failure of an incident such as slowing access to the internet banking url, non-functioning of some features of m-banking or even the cessation of the entire e-banking service. The proposed method to modify ANFIS with Fuzzy C-Means Clustering (FCM) approach is applied to detect four typical kinds of faults that may happen in the e-banking system, which are application response times, transaction per second, server utilization and network performance. Input data is obtained from the e-banking monitoring results throughout 2017 that become data training and data testing. The study shows that an ANFIS modeling with FCM optimized input has a RMSE 0.006 and increased accuracy by 1.27% compared to ANFIS without FCM optimization.

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Publication details

DOI
10.11591/ijece.v9i1.pp667-675
OpenAlex
W2939382708
Document type
article
Language
EN
Source
International Journal of Electrical and Computer Engineering (IJECE)
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