International Journal of Electrical and Computer Engineering
Vol 9, No 1: February 2019

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

Yuwono Abdillah (Bina Nusantara University)
Suharjito Suharjito (Bina Nusantara University)

Article Info

Publish Date
01 Feb 2019

Abstract

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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Journal Info
International Journal of Electrical and Computer Engineering
Website

Abbrev

IJECE

Publisher

Institute of Advanced Engineering and Science

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of ...