文章基本信息

标题：Cyber Profiling Using Log Analysis And K-Means Clustering
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作者：Muhammad Zulfadhilah ; Yudi Prayudi ; Imam Riadi 等
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2016
卷号：7
期号：7
DOI：10.14569/IJACSA.2016.070759
出版社：Science and Information Society (SAI)
摘要：The Activities of Internet users are increasing from year to year and has had an impact on the behavior of the users themselves. Assessment of user behavior is often only based on interaction across the Internet without knowing any others activities. The log activity can be used as another way to study the behavior of the user. The Log Internet activity is one of the types of big data so that the use of data mining with K-Means technique can be used as a solution for the analysis of user behavior. This study has been carried out the process of clustering using K-Means algorithm is divided into three clusters, namely high, medium, and low. The results of the higher education institution show that each of these clusters produces websites that are frequented by the sequence: website search engine, social media, news, and information. This study also showed that the cyber profiling had been done strongly influenced by environmental factors and daily activities.
关键词：thesai; IJACSA; thesai.org; journal; IJACSA papers; Clustering; K-Means; Log; Network; Cyber Profiling