ANALISIS KEBUTUHAN ACCESS POINT BERDASARKAN HISTORI TIAP LOKASI DI UNIVERISTAS ISLAM NEGERI SUNAN KALIJAGA MENGGUNAKAN METODE CLUSTERING ALGORITMA K-MEANS

RAZENDRA BINTANG KHARISMA, NIM. 13650043 (2017) ANALISIS KEBUTUHAN ACCESS POINT BERDASARKAN HISTORI TIAP LOKASI DI UNIVERISTAS ISLAM NEGERI SUNAN KALIJAGA MENGGUNAKAN METODE CLUSTERING ALGORITMA K-MEANS. Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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Abstract

Log analysis is the activity of analyzing the data collected in the transaction log, to investigate the information according to what we are looking for. The results of this log analysis can help us in improving customer satisfaction services or users contained in an agency / institution. An example of internet service is by looking at internet usage at any location at Sunan Kalijaga State Islamic University so that the actual access point requirement can be known. The data that will be retrieved and processed is the device data used and the data access point used. Data is taken every day for one week and is divided into three times, ie morning, noon and afternoon. To achieve the purpose of this research will be used clustering method to classify data that have similarities in one cluster, that is using K-Means algorithm. From the data that has been processed, there are five clusters that each share the access load received by an access point. The first cluster contains access points that have very high access loads, the second cluster contains access points that have a high access load, the third cluster contains access points that have normal access load, the fourth cluster contains access points that have low access load, Cluster Fifth contains access points that have very low access load.

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