Potential customer is someone who became accustomed to buying that formed through the changes and interactions that often during a certain period, by agreement between the seller and buyer. Mapping of potential customers by marketing analysts insurance is less accurate and difficult when the data storage media owned by large and multi dimensional. These problems required the mapping model that canclassify potential customers against certain insurance products. Model K-means algorithm can be used to mapping or classify customers based on profiles that have the potential to be an individual life insurance products with a level of accuracy reached 30%. Measurement similarity level, homogeneity and errors that are used in this study is a method of measuring cohesion and variations. Measurement method with a internal measurement methods with the Sum of Square Error.
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