Identification of Network Disruptions Using the Fuzzy K-Nearest Neighbor Algorithm in Case Based Reasoning at STMIK Pranata Indonesia

Abstract

Case-Based Reasoning (CBR) is a computer reasoning system that uses old knowledge to solve new problems. CBR provides solutions to new cases by looking at old cases that are closest to new cases. This would be very beneficial as it would eliminate the need to extract models as required by rule-based systems. The main problem in this research is the frequent disruption/difficulty for students and staff to connect to the network at the Indonesian institutional system. The method used is fuzzy K-Nearest Neighbor (FK-NN) is a variant of the K-Nearest Neighbor (KNN) method with fuzzy techniques. Using case based reasoning to make it easier for the system to reason, which prioritizes the use of information and previous knowledge to represent experience as a source of learning basis for reasoning. This system can help the IT team at STMIK Pranata Indonesia to more quickly handle types of network disturbances. Testing the system using a user acceptance test produces acceptable results and is used properly according to user needs. The scoring method uses a Likert scale with acceptance results of 94% with the criteria of strongly agree. The highest accuracy was obtained from test results with K = 5 with a value of 94.33%