The Implementation of Data Mining to Analyze the Consumer which is divided Into Class to Support the Decision Support System (DSS) in TB. 80 Majalengka

摘要

Consumers are an important asset to the company. This is the reason why a company must design and uses a good strategy to serve the consumer. With numerous consumers in a company, thus, the problem which the company face is to decide which one is the potential consumer. Using clustering method on data mining, the company can identify a potential consumer by grouping the consumers. Aims of the grouping the consumers are to know the consumers' behaviour and implementing an appropriate marketing strategy thus make the company earn a profit. This research discusses how the process of data mining from data of the consumers in TB. 80 which is a company run in selling building materials and has a goal to find a potential consumer, therefore, the company profit will increase. The process of Data Mining was started with preprocessing data (selecting, cleaning and transformation), then, on clustering phase use algorithm-means by deciding the number of clusters. The result of clustering from algorithm-means was used to group the consumers and formed a class based on frequency and monetary.