Determining Quality of Service (QoS) of End-User Internet Networks with Data Sniffing and Classification Algorithms

Abstract

The development of telecommunications technology in this world has changed very rapidly. Changes are made to access technology using the transmission media, which uses fiber optic technology, which has the advantage of being free from interference, large and fast data delivery capacity. An Internet Service Provider (ISP) is a provider of construction services and management of network infrastructure that always meets customer needs. Customer satisfaction with the services provided by ISP is also important in the era of increasingly tight market competition. Quality of Service (QoS) testing in internet networks needs to be done so that customers get optimal service. This study analyzes the quality of internet networks with fiber optic media on the end user side with the data sniffing method using Wireshark software that records video data traffic on the YouTube platform. The results of the data recording are processed using the QoS method with Throughput, Packet Loss, Delay, and Jitter parameters. The QoS assessment index is divided into Excellent, Good, Fair, and Poor classes according to the TIPHON standard. Data from these parameters is classified using the Naive Bayes, KNN, and Decision Tree methods. The results of applying the algorithms show the highest Accuracy value in the Decision Tree algorithm of 97%, while the highest Precision and Recall are in the KNN algorithm with values of 94% and 85%.