SALES TRANSACTION DATA EVALUATION INFORMATION SYSTEM USING CLUSTERING MODEL

Abstract

Sales evaluation exercises at instruments or trading enterprises with many outcomes and components are critical to determining the company's business development. Enterprise managers must know and evaluate sales data through reports on all branchesA trading business that has a department store, so it is essential to assess the sales trade. This sales evaluation knowledge system is necessary to promote store leadership in the deals evaluation strategy, which aims to aid the administration's decision-making process. The dealing data is evaluated using a clustering model to find a group of products selling well, especially in demand and not selling well. The algorithm used in clustering is by using K-Means. The sample data used is sales transaction data of 122 sales transaction data. Based on the results of the Davies Bouldin, it was found that the number of clusters with the best performance was 4 clusters with a Davies Blouldin value of -0.371. This analysis results in the sales data evaluation information system using the clustering model as an instrument for store managers to evaluate deals data at all department stores. The result of this method can be caused by the supervision as data in the decision-making method.