Facilitating resource allocation decision through Bibliomining: the case of UTM's library / Md Razib Karno

• Main Author: Karno, Md Razib
• Format: Thesis
• Language: English
• Published: 2015
• Subjects: Data mining; Electronic information resources
• Online Access: https://ir.uitm.edu.my/id/eprint/14010/1/TM_MD%20RAZIB%20KARNO%20IM%2015_5.pdf; https://ir.uitm.edu.my/id/eprint/14010/
• Institution: Universiti Teknologi Mara

Library has vastly developed and demand from the users, institutions, international organization needs and technology advancement has changed the library planning and decision making approach in many ways including library budgeting, human resource and infrastructure allocations. This research described (a) the investigation undertaken to examine the characteristics of data from data reservoirs regarding user/patron information and circulation information. (b) The information seeking to explore the patterns and trendsn among these data reservoirs using data mining analysis with about 957,224 borrowing history and overall 31,052 registered readers and 139,195 title author of books from the Universiti Teknologi Malaysia library since 2008 to 2010. (c) To study how constructed patterns and trends generate informed decisions on resource allocation for circulation function by using cluster analysis, frequency statistics, averages and aggregates and market basket analysis algorithm. This thesis highlights the finding of a research using data mining technique (CRISP-DM) to explore the potentials of the bibliographic data of an academic library. With nearly 1 million records of collection in various formats, the Library of Universiti Teknologi Malaysia has been chosen as the case study for the research. The data mining technique was adopted to explore the relationship among statistically patterned and clustered bibliographic data. Bibliomining are tools that can visualize how libraries manage their costs, staff activity, customer service, user needs, marketing, popular books, circulation, reference transaction, quality of collection, educational programs etc. Similar data mining techniques are suggested to be employed in different library settings and even enterprises as to make more effective use of organizational resources