UTHM Institutional Repository

Web usage mining in online community for evaluating staff performance

Arbaiy, Nureize and Ramli , Azizul Azhar and Suradi, Zurinah and Yusoff, Noor Haslina Web usage mining in online community for evaluating staff performance. In: International Conference on Information Technology and Multimedia (ICIMu 2005), 22-24 November 2005, Kajang.


Download (257kB)


Evaluating performances are perhaps the most obvious and most frequently cited issues in dealing with human capital in organizations. Recently, one of the ways to measure performance is through individual’s contribution on the Net. Activities captured by the web site, such as Online Community Portal, are useful information for measuring performance. In this case, data collected in the log file of a website server provide valuable information to web administrator and web designer. However, since the data accumulated were in large quantity, analyzing them create problem. Nevertheless, web mining can be utilized to minimize the problem, as it has been identified as one of the processes to analyze these types of data. The output from this process is identification of usage patterns of the user’s access. In this study, Association Rule Mining (ARM), a technique to mine data in log file is used. This technique allocates rules that satisfy user defined constraints on minimum support and confidence with respect to a given dataset. The result of the study shows that users in the faculty prefer to participate in the teaching and learning option as compared to other options. This result would simplify and assist appraiser and superior in the faculty to evaluate work performances of faculty members objectively and clearly. In addition, users of the website can actively participate and inform/share their work performances within the faculty.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: web usage mining; performance evaluation; data mining; online community
Subjects: Q Science > QA Mathematics > QA75 Calculating machines
Divisions: Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User: Normajihan Abd. Rahman
Date Deposited: 07 Nov 2012 03:56
Last Modified: 07 Nov 2012 03:56
URI: http://eprints.uthm.edu.my/id/eprint/2621
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item


Downloads per month over past year