<![CDATA[The number of car sales in e-commerce is currently increase along with the increasing use of the Internet in Indonesia. Purchases of Car in Indonesia are currently get higher, especially in used cars, which are a necessity for the community based on the odd-even system of car traffic policies currently applied in Jakarta. This research aims to study characteristics of clusters formed in e-commerce site to predict how are the car sales segmentation. Data is collected from big-two e-commerce site about car selling and buying in Indonesia. Clustering model is build using K-Means method and Davies Bouldin Index as evaluation of the clusters formed. The results show for both clusters, the first cluster has characteristic lowers sale price and older production year. The second cluster has higher price with latest production. From the model performance, evaluation from Davies Bouldin Index is quite good for both models. Keywords : Big Data, Clustering, K-Means, E-Commerce]]>
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