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Pingkan Awalia
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering Mathematics

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Penerapan Algoritma Tree Augmented Naive Bayesian pada Penentuan Peubah Penting Pingkan Awalia; Aji Hamim Wigena; Anang Kurnia
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 11, No 2 (2011)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v11i2.1053

Abstract

In the era of free market competition today, improving product quality is very important. Consumerpreferences through product level of analysis is one method that many manufacturers conducted toevaluate the product. Multivariable regression is a statistical method used to determine the importantvariables. The weakness of this method is the strict assumption. This problem will be completed bythe method of bayesian networks. There are several algorithms to build the BN. This study uses TANand NB because of its simplicity. This study shows that the most accurate method at the chosen levelof classification accuracy is the TAN by 83%. The importance variable is the aspect liking of strengthof after taste.
Co-Authors Aji Hamim Wigena Anang Kurnia