Jamil, Jastini and Mohd Shaharanee, Izwan Nizal (2014) Comparative analysis of data mining techniques for business data. In: 3rd International Conference on Quantitative Sciences and its Applications (ICOQSIA 2014), 12–14 August 2014, Langkawi, Kedah Malaysia.

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Abstract

Data mining is the process of employing one or more computer learning techniques to automatically analyze and extract knowledge from data contained within a database.Companies are using this tool to further understand their customers, to design targeted sales and marketing campaigns, to predict what product customers will buy and the frequency of purchase, and to spot trends in customer preferences that can lead to new product development.In this paper, we conduct a systematic approach to explore several of data mining techniques in business application.The experimental result reveals that all data mining techniques accomplish their goals perfectly, but each of the technique has its own characteristics and specification that demonstrate their accuracy, proficiency and preference.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	ISBN: 978-0-7354-1274-3
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Divisions:	School of Quantitative Sciences
Depositing User:	Mr. Jastini Mohd Jamil
Date Deposited:	17 May 2015 04:49
Last Modified:	19 May 2016 01:06
URI:	https://repo.uum.edu.my/id/eprint/14140

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