Robust Demand Estimation of Choice Models for Personalized Offers Using Sales Transaction Data

This paper analyzes and synthesizes the fundamentals of discrete choice models. This paper alsodiscusses the basic concept and theory underlying the econometrics of discrete choice, specific choicemodels, estimation method, model building and tests, and applications of discrete choice models. Thiswork highlights the relationship between economic theory and discrete choice models: how economictheory contributes to choice modeling and vice versa. Keywords: Discrete choice models; Random utility maximization; Decision makers; Utility function;Model formulation

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Pemanfaatan Metode K-Means Dalam Penentuan Persediaan Barang

PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic ◽

10.33558/piksel.v6i1.1398 ◽

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.

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