Surbakti, Herison and Ta'a, Azman (2019) Cognitive approach using SFL theory in capturing tacit knowledge in business intelligence. In: 2019 International Conference on Data and Software Engineering (ICoDSE), 13-14 Nov. 2019, Pontianak, Indonesia, Indonesia.

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Abstract

The complexity of Business Intelligence (BI) processes need to be explored in order to ensure BI system properly treats the tacit knowledge as part of data source in BI framework. Therefore, a new approach in handling tacit knowledge in BI system still needs to be developed. The library is an ideal place to gather tacit knowledge. It is a place full of explicit knowledge stored in various bookshelves. Nevertheless, tacit knowledge is very abundant in the head of the librarians. The explicit knowledge they gained from education in the field of libraries and information was not sufficient to deal with a complex and contextual work environment. Complexity comes from many interconnected affairs that connect librarians with the surrounding environment such as supra-organizations, employees, the physical environment, and library users. This knowledge is contextual because there are various types of libraries and there are different types of library users who demand different management. Since tacit knowledge hard to capture, we need to use all possible sources of externalization of tacit knowledge. The effort to capture this knowledge is done through a social process where the transfer of knowledge takes place from an expert to an interviewer. For this reason, it is important for the interview process to be based on SFL theory (Systemic Functional Linguistics).

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	INSPEC Accession Number: 19612782
Uncontrolled Keywords:	Business Intelligence, Tacit Knowledge, SFL theory
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	School of Computing
Depositing User:	Mrs. Norazmilah Yaakub
Date Deposited:	09 Sep 2020 07:10
Last Modified:	09 Sep 2020 07:10
URI:	https://repo.uum.edu.my/id/eprint/27438

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