Open AccessThe Implementation of Data Mining to Analyze the Consumer which is divided Into Class to Support the Decision Support System (DSS) in TB. 80 Majalengka
Author(s) -
Deffy Susanti
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/662/2/022116
Subject(s) - cluster analysis , profit (economics) , class (philosophy) , asset (computer security) , process (computing) , computer science , business , marketing , data mining , artificial intelligence , economics , computer security , microeconomics , operating system
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 pre-processing 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.