An improvement of Knowledge Discovery Database (KDD) framework for effective decision

• Main Authors: Rahman, F. A., Desa, M. I., Wibowo, A., Haris, N. A.
• Format: Article
• Published: Asian Network for Scientific Information 2016
• Subjects: T Technology (General)
• Online Access: http://eprints.utm.my/id/eprint/74332/; https://www.scopus.com/inward/record.uri?eid=2-s2.0-84999098066&doi=10.3923%2fjai.2016.72.77&partnerID=40&md5=d812ac49eb549416d77261ab678c72b0

In this study, an understanding and a review of Knowledge Discovery Database (KDD) development and its applications in tire maintenance are highlighted. Even though data mining has been successful in becoming a major component of various business processes and applications, the benefits and real-world expectations are very important to consider. It is also surprising to note that very little is known to date about the usefulness of applying knowledge discovery in transport related research. From the literature, the frameworks for carrying out knowledge discovery and data mining have been revised over the years to meet the business requirements. The Domain Driven Data Mining (DDDM) is one of the KDD frameworks often used for this purpose. In this study, we apply DDDM-KDD for formulating effective tire maintenance strategy within the context of a Malaysian's logistics company. We also discussed the weaknesses of the results from DDDM-KDD and emphasize the important of using the next generation of KDD framework Actionable Knowledge Discovery (AKD) for an effective decision. The direction flow of research, research methods use and contribution of research also are highlighted.