IMPLEMENTASI ALGORITMA K-MEANS DENGAN MENGGUNAKAN MODEL RFM UNTUK SEGMENTASI PELANGGAN
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Putriana, Deby
Sudirman, M. Yoga Distra
Palupiningsih, Pritasari
Sudirman, M. Yoga Distra
Palupiningsih, Pritasari
Subject
Teknik Informatika
Datestamp
2022-09-26 07:52:28
Abstract :
Customer is one of the most important elements in the selling of goods and services because the profit generated by the companies or business leaders. The high prescriptive rate for customers with a high data will take considerable time in determining customer rates as in selecting data which attributes should be desired first as parameters to study and where algorithms K-Means has been developed and RFM methods (recancy, frequency Monetary) until factor is used by customers more efficiently. K-means algorithm is used systemizing the customer and RFM's Methode of data as using variable. The salable assets used in this study are data from the chemical Farma's company trading was authenticated over five months of sales data cataloged by a three-cluster set, producing results on cluster one 54 members. Cluster two 24 members and an imster three 163 members. For testing the optimized composite values that have been done using Davies Bouldin Index (DBI). Counting process of DBI as about 0.96 to the quality conclusion has been done better
Customer is one of the most important elements in the selling of goods and services because the profit generated by the companies or business leaders. The high prescriptive rate for customers with a high data will take considerable time in determining customer rates as in selecting data which attributes should be desired first as parameters to study and where algorithms K-Means has been developed and RFM methods (recancy, frequency Monetary) until factor is used by customers more efficiently. K-means algorithm is used systemizing the customer and RFM's Methode of data as using variable. The salable assets used in this study are data from the chemical Farma's company trading was authenticated over five months of sales data cataloged by a three-cluster set, producing results on cluster one 54 members. Cluster two 24 members and an imster three 163 members. For testing the optimized composite values that have been done using Davies Bouldin Index (DBI). Counting process of DBI as about 0.96 to the quality conclusion has been done better
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