Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/8130
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dc.contributor.authorFauziah Abdul Rahman, Mohammad Ishak Desa-
dc.contributor.authorAntoni Wibowo, Norhaidah Abu Haris-
dc.date.accessioned2014-10-30T05:09:19Z-
dc.date.available2014-10-30T05:09:19Z-
dc.date.issued2014-10-30-
dc.identifier.urihttp://localhost/xmlui/handle/123456789/8130-
dc.descriptionConference venue:Yogjakartaen_US
dc.description.abstractIn this paper, an understanding and a review of data mining (DM) development and its applications in logistics and specifically transportation 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 data mining 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 expectations. In this paper, we apply CRISP-DM for formulating effective tire maintenance strategy within the context of a Malaysian’s logistics company. The results of applying CRISP-DM for tire maintenance decisions are presented and discussed.en_US
dc.subjectData Miningen_US
dc.subjectKnowledge Discovery Database- Data Mining (KDD-DM)en_US
dc.subjectDomain-Driven Data Mining (DDDM)en_US
dc.subjectActionable Knowledge Discovery (AKD)en_US
dc.subjectActionable Knowledge Discovery (AKD)en_US
dc.titleKnowledge Discovery Database (KDD)-Data Mining Application in Transportationen_US
dc.conference.nameProceeding of International Conference on Electrical Engineering Computer Science and Informaticsen_US
dc.conference.year2014en_US
Appears in Collections:Conference Paper

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