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.
Highlights
INTRODUCTIONThe item delivery service industry occupies one of the central positions in the economy of modern society and is a driver of doing business both long and near
At present, online business is very supportive of one’s economy
Development of online business which is supported by the availability of item delivery services is very suitable in Indonesia, considering that Indonesia is a developing country which consists of a vast archipelago
Summary
The item delivery service industry occupies one of the central positions in the economy of modern society and is a driver of doing business both long and near. This certainly supports an increase in prosperity, especially in developed countries. Development of online business which is supported by the availability of item delivery services is very suitable in Indonesia, considering that Indonesia is a developing country which consists of a vast archipelago. One of these methods is allocation by a strict method, where data items are expressly stated as one cluster member and not a member of another cluster This type of method is called k-means.
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