Development of a manufacturing industry success rate analyzer using data mining technique

Mazlan, E.M. and Rahman, S. and Ahmad, R. and Kasbon, R. (2010) Development of a manufacturing industry success rate analyzer using data mining technique. In: UNSPECIFIED.

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Abstract

Starting up new businesses can be resource consuming. There are risks involved whenever new businesses are to be set up. This paper presents the development of a success rate analyzer to calculate the successful rate of setting up new manufacturing businesses particularly in Perak, Malaysia. Demographic data of Perak population is used and the data undergoes data mining process using the clustering technique and linear regression methods in analyzing the success rate of a manufacturing industry in Perak. With the result given by the application, new entrepreneurs can decide suitable locationldistrict to set up the manufacturing business. © 2010 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 2; Conference of 2010 International Symposium on Information Technology, ITSim'10 ; Conference Date: 15 June 2010 Through 17 June 2010; Conference Code:81915
Uncontrolled Keywords: Business success; Clustering; Clustering techniques; Data mining process; Data mining techniques; Demographic data; Linear regression methods; Malaysia; Manufacturing business; Manufacturing industries, Data mining; Information technology; Linear regression; Manufacture; Mining; Population statistics, Cluster analysis
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 15:49
Last Modified: 09 Nov 2023 15:49
URI: https://khub.utp.edu.my/scholars/id/eprint/1040

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