The Mapping of Access Point Workloads at UIN Sunan Kalijaga Based on Log Analysis using K-Means Algorithm

Razendra Bintang Kharisma, Ahmad Subhan Yazid


This study aims to map the use of access points based on the log of usage in several locations in the UIN Sunan Kalijaga. The analyzed data are access point records taken three times a day for one week working hours. The data obtained was processed and clustered using the K-Means algorithm. There are five clusters obtained from the processed data, each of which divides the number of access loads from an access point. The results of clustering provide a recommendation on which locations need to be added to access points that it can improve institutional user


Access loads; Cluster; K-means; Log; Number of users

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