SEGMENTASI PELANGGAN MENGGUNAKAN METODE FUZZY C-MEANS CLUSTERING BERDASARKAN MODEL RFM (STUDI KASUS: PT. KALUNGGA JAYA ABADI)

MONITA, TISA and Tania, Ken Ditha (2020) SEGMENTASI PELANGGAN MENGGUNAKAN METODE FUZZY C-MEANS CLUSTERING BERDASARKAN MODEL RFM (STUDI KASUS: PT. KALUNGGA JAYA ABADI). Undergraduate thesis, Sriwijaya University.

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Abstract

Tight competition in the business field motivates companies to optimally improve service management for customers by grouping customers into groups and determining appropriate and effective marketing strategies for each group. The customer grouping can be done through a clustering approach with the Fuzzy C-Means algorithm. PT Kalungga Jaya Abadi is a motorcycle spare parts distributor specializing in tire in South Sumatra which already has an accounting information system. However, customer data and transaction data that has not been used to get customer value and segmentation So that the clustering process with the Fuzzy C-Means method is done to group customers with similar RFM (Recency, Frequency, and Monetary) value characteristics. The data used are transaction data for 2018, with 254 customers and the results of the cluster using the elbow method are 2 clusters. The cluster validity test uses the Modified Partition Coefficient, Dunn Index, Connectivity and Silhoutte Width methods. The results of the clustering process are used as a dashboard visualization using Shiny Dashboard in the R Studio tools.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Segmentasi pelanggan, RFM,Clustering, Fuzzy C-Means, Elbow Method, CRISP-DM
Subjects:	T Technology > T Technology (General) > T57-57.97 Applied mathematics. Quantitative methods > T57.5 Data processing Cf. HF5548.125+ Business data processing Operations research. Systems analysis T Technology > T Technology (General) > T58.5-58.64 Information technology > T58.6.E9 Management information systems -- Congresses. T Technology > T Technology (General) > T58.6-58.62 Management information systems > T58.62 Decision support systems Cf. HD30.213 Industrial management
Divisions:	09-Faculty of Computer Science > 57201-Information Systems (S1)
Depositing User:	Users 5718 not found.
Date Deposited:	15 Apr 2020 04:00
Last Modified:	15 Apr 2020 04:00
URI:	http://repository.unsri.ac.id/id/eprint/28970

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