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All Journal PIONIR: Jurnal Pendidikan EDUTECH: Jurnal Ilmu Pendidikan dan Ilmu Sosial Quantitative Economics Journal Jurnal Masharif al-Syariah: Jurnal Ekonomi dan Perbankan Syariah LIABILITIES (JURNAL PENDIDIKAN AKUNTANSI) Biblio Couns : Jurnal Kajian Konseling dan Pendidikan Hasil Pengabdian Kepada Masyarakat WIDYABHAKTI Jurnal Ilmiah Populer Ihsan: Jurnal Pengabdian Masyarakat Jupeko (Jurnal Pendidikan Ekonomi) Jurnal Penelitian, Pendidikan dan Pengajaran: JPPP Education Journal of Indonesia (EJI) EduInovasi: Journal of Basic Educational Studies Hanif Journal of Information Systems
Dian Novianti Sitompul
Universitas Muhammadiyah Sumatera Utara
Religion Humanities Computer Science & IT Economics, Econometrics & Finance Education Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Social Sciences Other

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Journal : Hanif Journal of Information Systems

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Application of Fuzzy C-Means Algorithm for Clustering Customers Oktaviana Nirmala Purba; Dian Novianti Sitompul; Tua Holomoan Harahap; Sri Rahmah Dewi Saragih; Rizka Fahruza Siregar
Hanif Journal of Information Systems Vol. 1 No. 1 (2023): August Edition
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/hanif.v1i1.8

Abstract

Today's fierce business competition requires companies to focus on the needs desired by consumers.This makes companies have to think about how to manage customer data so that it can be utilized properly for the development of marketing strategies.And Grouping (cluster) customers based on their respective characteristics can be an alternative in solving these problems.In clustering (cluster) customers there are several data mining clustering methods that can be used, one of which is the Fuzzy C-Means (FCM) method. FCM is a clustering algorithm where one object can be a member of several clusters and FCM cluster boundaries are vague. The output of FCM is a row of cluster centers and several degrees of membership for each data point. In this clustering, customers will be divided into 4 customer clusters namely Golden, Silver, Bronze, and Iron with the variables used as a reference are the final purchase date, purchase frequency and total purchase. The data used is customer transaction data for the period September - December 2015. The total data is 709 transactions from 75 customers. After the data is processed with the Fuzzy C-Means method, the final results show that the iteration ends at the 30th iteration with a change in the objective function of 9.8. The resulting customer clusters are Golden: 27, Silver: 15, and Bronze: 33 with a cluster validity of 0.596277.
Co-Authors Ayrin Rissky Amalia Citra Aulia Rahmadani Dewi Hanifah Dewi Juni Artha Faisal Rahman Dongoran Indah Wikiya Sari Isra Hayati Mutia Febriyana Mutia Ferbriyana Nur Sakinah Oktaviana Nirmala Purba Pipit Putri Hariani MD Putri Rahayu Ramayani Ramayani Rizka Fahruza Siregar Rosdiana Saragih Sri Rahma Dewi Saragih Tua Holomoan Harahap