Evaluation of Computer Network Simulation Applications to Support Online Learning

Abstract

Computer network learning is learning that prioritizes practice compared to theory to be able to understand the material more clearly. Therefore, computer network learning requires real learning media to support learning effectiveness. However, because the cost of procuring computer network learning media is quite large, it is one of the main obstacles. By using a computer network simulator application is one way to overcome these obstacles. At this time there are several computer network simulator applications that can be used to support computer network learning activities to run efficiently. In this study, researchers evaluate and analyze several network simulation applications, to find out which applications are more efficient to use in learning computer networks, seen from the application capabilities in IP Address configuration, Subnetting, Routing. This study uses the observation method of computer network simulator applications that have been determined, namely the application of (1) Cisco Packet Tracer, (2) GNS3, (3) EVE-NG, (4) Boson Netsim, using the LORI research instrument version 1.5. This research has several stages, namely data collection, data reduction, scoring, data presentation, drawing conclusions and measured using a Likert scale. The results of this study indicate that the application (1) Cisco Packet Tracer ranks first with a value of 89.1%, (2) Boson Netsim is in second place with a score of 86.6%, (3) GNS3 ranks third with a value of 85.4%, (4) EVE-NG ranks fourth or lowest with a score of 83.3%.