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

Risma Restu Ramadina, Tacbir Hendro Pudjiantoro, Irma Santikarama

Abstract

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.

Keywords

CRM; Rekomendation; Transaction

References

E. P. Denniswara, “Pengaruh Kualitas Produk, harga dan Promosi terhadap Intensi membeli ulang produk My Idea,” Strateg. Segmentasi Pasar Dan Promosi Dalam Meningkat. Vol. Penjualan, vol. 1, p. 10, 2018.

Z. Soltani and N. J. Navimipour, “Customer relationship management mechanisms: A systematic review of the state of the art literature and recommendations for future research,” Comput. Human Behav., vol. 61, pp. 667–688, 2016.

A. Faisal, Wina, “PEMBANGUNAN SISTEM CUSTOMER RELATIONSHIP MANAGEMENT PADA PT.CENTRAL GEORGETTE NUSANTARA,” Tek. Inform., pp. 431–438, 2017.

D. Listriani, A. H. Setyaningrum, and F. Eka, “PENERAPAN METODE ASOSIASI MENGGUNAKAN ALGORITMA APRIORI PADA APLIKASI ANALISA POLA BELANJA KONSUMEN (Studi Kasus Toko Buku Gramedia Bintaro),” J. Tek. Inform., vol. 9, no. 2, pp. 120–127, 2018.

Santhosh M, “CRM Practices in Electrical Accessories Industry : A Study on Akarui Green Energy Solution,” vol. 1, no. 12, pp. 23–28, 2018.

P. Zerbino, D. Aloini, R. Dulmin, and V. Mininno, “Big Data-enabled Customer Relationship Management: A holistic approach,” Inf. Process. Manag., vol. 54, no. 5, pp. 818–846, 2018.

X. Yuan, “An improved Apriori algorithm for mining association rules,” AIP Conf. Proc., vol. 1820, no. March 2017, 2017.

I. Viktoratos, A. Tsadiras, and N. Bassiliades, “Combining community-based knowledge with association rule mining to alleviate the cold start problem in context-aware recommender systems,” Expert Syst. Appl., vol. 101, pp. 78–90, 2018.

R. Rekik, I. Kallel, J. Casillas, and A. M. Alimi, “Assessing web sites quality: A systematic literature review by text and association rules mining,” Int. J. Inf. Manage., vol. 38, no. 1, pp. 201–216, 2018.

K. N. Wijaya, “Analisa Pola Frekuensi Keranjang Belanja dengan Algoritma Apriori,” Comput. Sci., vol. 3, no. 1, pp. 9–12, 2017.

M. S. Mustaqbal, R. F. Firdaus, and H. Rahmadi, “PENGUJIAN APLIKASI MENGGUNAKAN BLACK BOX TESTING BOUNDARY VALUE ANALYSIS (Studi Kasus : Aplikasi Prediksi Kelulusan SNMPTN),” Teknol. Inf., vol. I, no. 3, pp. 31–36, 2015.

U. I. Sari, I. Permana, and F. N. Salisah, “Sistem Pendukung Keputusan Berbasis Rule Untuk Pemilihan Model Hijab,” Semin. Nas. Teknol. Inf. Komun. dan Ind., vol. 9, pp. 138–143, 2017.

DOI: https://doi.org/10.36054/jict-ikmi.v19i1.143

Refbacks

  • There are currently no refbacks.