APLIKASI ANALISIS DISKRIMINAN DALAM MENENTUKAN KEPUTUSAN PEMBELIAN PRODUK McCafe (Studi Kasus: McDonald’s Jimbaran Bali)

##plugins.pubIds.doi.readerDisplayName## https://doi.org/10.24843/MTK.2018.v07.i01.p184

Abstrak

McDonald’s is one of fast food company that is growing rapidly. McDonald’s continues to innovate to satisfy customers. It introduced the concept of a cafe with the name McCafe. Because of the competition with other fast food restaurants, McDonald’s needs to improve the quality of McCafe favored by customers. Thus, this research was conducted to aim at getting the indicators that are best describing customers characteristic. This research used discriminant analysis methods. Discriminant analysis was used to classify customers into groups of loyal customers or non loyal customers.. The indicators that distinguished the decision of the customer to buy McCafe Jimbaran product were affordable prices and locations that are easily accessible to customers. The formed discriminant function had an accuracy of 91,67 percent in classifying the customers.

##plugins.generic.usageStats.downloads##

##plugins.generic.usageStats.noStats##

##submission.authorBiographies##

##submission.authorWithAffiliation##

Jurusan Matematika, Fakultas MIPA – UniversitasUdayana

##submission.authorWithAffiliation##

Jurusan Matematika, Fakultas MIPA – UniversitasUdayana

##submission.authorWithAffiliation##

Jurusan Matematika, Fakultas MIPA – UniversitasUdayana

##submission.authorWithAffiliation##

Jurusan Matematika, Fakultas MIPA – UniversitasUdayana

Diterbitkan
2018-02-03
##submission.howToCite##
RAMADHAN, TRISNA et al. APLIKASI ANALISIS DISKRIMINAN DALAM MENENTUKAN KEPUTUSAN PEMBELIAN PRODUK McCafe (Studi Kasus: McDonald’s Jimbaran Bali). E-Jurnal Matematika, [S.l.], v. 7, n. 1, p. 50-55, feb. 2018. ISSN 2303-1751. Tersedia pada: <https://ojs.unud.ac.id/index.php/mtk/article/view/37606>. Tanggal Akses: 14 oct. 2025 doi: https://doi.org/10.24843/MTK.2018.v07.i01.p184.
Bagian
Articles

##plugins.generic.recommendByAuthor.heading##

1 2 3 4 > >>