CLUSTERING FOR ITEM DELIVERY USING RULE-K-MEANS

Abstract

In this paper, we introduce an alternative approach as model for cluster analysis. The data were analyzed by rule-k-means algorithm. It's combine between k-means algorithm and rules. As an application, we use the simulate of item delivery data to classify items based on destination addresses. The goal is to map the item based on type of delivery vehicle. The clustering can be used as a recommendation to the item delivery service company.