Sistem Customer Relationship Management (CRM) Menggunakan Metode Asosiasi Algoritma Apriori Untuk Menentukan Rekomendasi Produk

Jurnal ICT : Information Communication & Technology

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Title Sistem Customer Relationship Management (CRM) Menggunakan Metode Asosiasi Algoritma Apriori Untuk Menentukan Rekomendasi Produk
Creator Ramadina, Risma Restu
Pudjiantoro, Tacbir Hendro
Santikarama, Irma
Subject CRM; Rekomendasi; Transaksi
Description There are companies in the fashion sector that sell clothing for both women and men at affordable prices and quality. Currently, there are many competitors everywhere, especially in the Cimahi City area. The current SR Fashion Store boutique has a target of increasing the number of customers and retaining existing customers. However, because this fashion company has problems, namely delivery and determining recommendations that are directly in place, resulting in inconvenience for customers who make recommendations that are not in accordance with the tastes of these customers, because the services provided by the boutique have not been maximized causing customer loyalty to decline. Solutions to overcome these problems must be made a Customer Relationship Management System (CRM) that can be managed by a fashion company besides that the system to be built can also be accessed by customers. The system built will provide recommendations based on the customer's transaction history. To provide recommendations in a system by applying the association method using a priori algorithm, these recommendations are received by member subscribers via email messages. By looking at the transaction history of a customer who has made transactions more than five times, the recommendation will automatically be sent to the customer. The application of the association method using this a priori algorithm shows an attitude to determine product recommendations based on transaction history, by taking 5 product samples and 7 transaction histories in one member producing 2 recommendation rules with a support value of 42.8% and 75% trust.
Publisher STMIK IKMI Cirebon
Date 2020-09-09
Type info:eu-repo/semantics/article
Peer-reviewed Article
Format application/pdf
Source Jurnal ICT : Information Communication & Technology; Vol 19, No 1 (2020): JICT-IKMI, Juli 2020; 50-59
Language eng
Rights Copyright (c) 2020 Jurnal ICT : Information Communication & Technology

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