scholarly journals A Parallel Method for Scalable Anonymization of Transaction Data

2015 ◽  
Author(s):  
Neelam Memon ◽  
Grigorios Loukides ◽  
Jianhua Shao
Keyword(s):  
Parallel Method ◽  
Transaction Data

Pemanfaatan Metode K-Means Dalam Penentuan Persediaan Barang

2018 ◽  
Vol 6 (1) ◽  
pp. 41-48
Author(s):  
Santoso Setiawan
Keyword(s):  
Data Mining ◽  
Stock Management ◽  
Transaction Data ◽  
Business People ◽  
Cluster Data ◽  
Data Clusters ◽  
Inventory Strategy ◽  
Transactional Data

Abstract   Inaccurate stock management will lead to high and uneconomical storage costs, as there may be a void or surplus of certain products. This will certainly be very dangerous for all business people. The K-Means method is one of the techniques that can be used to assist in designing an effective inventory strategy by utilizing the sales transaction data that is already available in the company. The K-Means algorithm will group the products sold into several large transactional data clusters, so it is expected to help entrepreneurs in designing stock inventory strategies.   Keywords: inventory, k-means, product transaction data, rapidminer, data mining   Abstrak   Manajemen stok yang tidak akurat akan menyebabkan biaya penyimpanan yang tinggi dan tidak ekonomis, karena kemungkinan terjadinya kekosongan atau kelebihan produk tertentu. Hal ini sangat berbahaya bagi para pelaku bisnis. Metode K-Means adalah salah satu teknik yang dapat digunakan untuk membantu dalam merancang strategi persediaan yang efektif dengan memanfaatkan data transaksi penjualan yang telah tersedia di perusahaan. Algoritma K-Means akan mengelompokkan produk yang dijual ke beberapa cluster data transaksi yang umumnya besar, sehingga diharapkan dapat membantu pengusaha dalam merancang strategi persediaan stok.   Kata kunci: data transaksi produk, k-means, persediaan, rapidminer, data mining.

scholarly journals High-resolution assessment of environmental benefits of dockless bike-sharing systems based on transaction data

2021 ◽  
Vol 296 ◽  
pp. 126423
Author(s):  
Aoyong Li ◽  
Kun Gao ◽  
Pengxiang Zhao ◽  
Xiaobo Qu ◽  
Kay W. Axhausen
Keyword(s):  
High Resolution ◽  
Environmental Benefits ◽  
Transaction Data ◽  
Bike Sharing
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