SEGMENTASI PENJUALAN PRODUK SPARE PART SEBAGAI POLA PRILAKU PEMBELI DENGAN PENDEKATAN MODEL FUZZY SUBTRACTIVE CLUSTERING (Studi Kasus : PT. United Tractors,Tbk Cabang Padang)
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
ARVIO, YOZIKA
Sangadji, Iriansyah BM
Kusuma, Dine Tiara
Sangadji, Iriansyah BM
Kusuma, Dine Tiara
Subject
Teknik Informatika
Datestamp
2020-02-28 12:05:40
Abstract :
PT United Tractors is a distributor of heavy equipment that runs the business through three business units, namely construction machinery, mining and mining. One of the branch offices is increasing its trade volume branch, known by the number of sales each year. Then it is necessary to know the product sales segmentation needs, keinginanan and the characteristics of the customers in the market by using the process method of fuzzy subtractive clustering clustering to group a number of data into several clusters which have similarities to one and other, fuzzy subtractive clustering this will form the number of clusters or rules automatically without need to be initialized at the beginning. The data used is a data product sales spare parts by 2015 in PT. UT branch, namely the data quantity, net value and cogs. The result of the process of clustering pattern behavior of buyers in quarter 1 and quarter 2 number of cluster 2 cluster is formed while the quarter 3 and quarter 4 number of cluster 3 cluster is formed. Based on the results of this study the behavior pattern then buyers are likely to rise on quarter 3 and quarter 4.
PT United Tractors is a distributor of heavy equipment that runs the business through three business units, namely construction machinery, mining and mining. One of the branch offices is increasing its trade volume branch, known by the number of sales each year. Then it is necessary to know the product sales segmentation needs, keinginanan and the characteristics of the customers in the market by using the process method of fuzzy subtractive clustering clustering to group a number of data into several clusters which have similarities to one and other, fuzzy subtractive clustering this will form the number of clusters or rules automatically without need to be initialized at the beginning. The data used is a data product sales spare parts by 2015 in PT. UT branch, namely the data quantity, net value and cogs. The result of the process of clustering pattern behavior of buyers in quarter 1 and quarter 2 number of cluster 2 cluster is formed while the quarter 3 and quarter 4 number of cluster 3 cluster is formed. Based on the results of this study the behavior pattern then buyers are likely to rise on quarter 3 and quarter 4.
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