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Identifying Purchasing Patterns of Arab and Malaysian Students Using Data Mining Technique

Abuhamdah, Anmar Fakhri Moh'd (2006) Identifying Purchasing Patterns of Arab and Malaysian Students Using Data Mining Technique. Masters thesis, Universiti Utara Malaysia.

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Abstract

Currently, Universiti Utara Malaysia (UUM) has a significant number of international students. Since they are from various background and culture, their preferences towards purchasing products are different. This study intends to identify purchasing patterns of 2 groups of students: Arab and Malaysian. The 2 groups have been chosen because they represent the major groups of the postgraduate students. A questionnaire has been constructed and used to collect data. The sample of data consists of postgraduate students from Arab and Malaysia. The total number of postgraduate students is 2122 and the total number of the sample data is 547 (30% of the population). Apriori Algorithmn, which is a popular data mining technique has been used to identify the purchasing patterns. The study discovered that items such as fruits, vegetables, drinks and pickled food are frequently purchased by the Arabs. The Malaysians, however prefer items such as Pickled Foods, Snack Foods, and Other Stuff. A more comprehensive work in the future is suggested so that result obtained can be generalized. The study has been successful achieving all objectives. It is hope that the results could be use to strategic UUM as the patterns identified could be used to strategize UUM's retailing businesses and at the same time provide adequate facilities in terms of selling preferred products to its consumers.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Purchasing Patterns, Postgraduate Students, Data Mining
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty and School System > Faculty of Information Technology
Depositing User: Ms Rohaida Rohani
Date Deposited: 04 Jul 2010 01:04
Last Modified: 24 Jul 2013 12:13
URI: http://etd.uum.edu.my/id/eprint/1823

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