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Laila Isyriyah
Informatika, Sekolah Tinggi Informatika & Komputer Indonesia, Malang, Indonesia
Education

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Prediksi Loyalitas Pelanggan Pada Fast Moving Consumer Goods Menggunakan Klasifikasi Metode C4.5 Laila Isyriyah; Imam Baihaqi; Febry Eka Purwiantono
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 13 No 02 (2023): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v13i02.1115

Abstract

Instant noodles are one of the food products from the Fast Moving Customer Goods (FMCG) industry which is a fairly large industry in Indonesia. However, competition is inevitable. So to win the competition from other companies, company management is required to determine a strategi to maintain customer loyalty. Therefore, the purpose of this study is to create an application to predict customer loyalty and determine the influential attributes by applying Data Mining Classification in the form of a desicion tree. The application method used in Classification for prediction is the C4.5 method. In the C4.5 algorithm, entropy and information gain are calculated where customer loyalty is the attribute of destination (class), while price, packaging, taste, cariety, advertising, distribution, and quality are the source attributes to obtain the root node and other nodes. The results of the study show that the application using the C4.5 method produces an accuracy of 95.5%, so the C4.5 method can be used to assist the management of instant noodle companies in order to determine strategies to maintain consumer loyalty.
Co-Authors Febry Eka Purwiantono Imam Baihaqi