Mohammad Ishak Desa
Faculty of Computing, Universiti Teknologi Malaysia, Johor

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Journal : Proceeding of the Electrical Engineering Computer Science and Informatics

Knowledge Discovery Database (KDD)-Data Mining Application in Transportation Fauziah Abdul Rahman; Mohammad Ishak Desa; Antoni Wibowo; Norhaidah Abu Haris
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 1: EECSI 2014
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (722.936 KB) | DOI: 10.11591/eecsi.v1.357

Abstract

In 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.