Web usage mining for determining a website’s usage pattern : a case study of metropolitan electricity authority (MEA) | |
| Author | Panunsiya Rawira |
| Call Number | AIT RSPR no.IM-23-06 |
| Subject(s) | Web usage mining--Case studies Data mining--Case studies |
| Note | A research study submitted in partial fulfillment of the requirements for the degree of Master of Science in Information Management |
| Publisher | Asian Institute of Technology |
| Abstract | Web usage mining is a crucial research spot that aims to uncover user behavior patterns from web log data. It is a subset of data mining. This technique consisted of four sub-tasks: data collection, pre-processing, pattern discovery, and pattern analysis. This study examined web usage mining to discover online users' usage patterns and used the results to redesign and improve the Metropolitan Electricity Authority (MEA) website. This study aims to help online customers obtain a better experience. A dataset was collected from the MEA website. Various algorithms, including association rule mining (Apriori and FP-Growth) and sequential pattern mining (GSP and Prefix-Span), were used to mine the web usage data. The website prototype was developed based on the web usage mining results. The first 30 frequently visited patterns of web usage mining results were selected for analysis and to develop a prototype. It revealed that most pages were accessed directly. Most users were interested in alternative energy information, the FT rate, the power outage announcement page, and reducing electric expenses, including government electric assistance news, residential electric rates, and infographics on reducing electric costs. Furthermore, the analysis indicated that customers were interested in making online processes, such as using the contact-us feature, downloading forms, and calculating their electric expenses. A survey was conducted with 30 participants (50% male and 50% female). The results were compared with the usage data from the weblog, and a Welch's t-test was utilized to evaluate the outcomes. The user's usage time before improving the website from the first three frequently visited patterns is 201.65, 360.99, and 403.96 seconds. In comparison, the users' usage time after improving the website is 25.66, 37.20, and 48.83 seconds, respectively. The findings indicated that the newly implemented website, based on the user usage patterns, was more effective and reduced the user's usage time. Moreover, future research implications of these studies are discussed. |
| Year | 2023 |
| Type | Research Study Project Report (RSPR) |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Information Management (IM) |
| Chairperson(s) | Vatcharaporn Esichaikul; |
| Examination Committee(s) | Teerawat Issariyakul;Chutiporn Anutariya; |
| Scholarship Donor(s) | MEA-AIT Academic Cooperation Program;AIT Scholarships; |
| Degree | Research studies project report (M. Sc.) - Asian Institute of Technology, 2023 |