Data Mining Implementation on Choosing Potential Customers Using K-Means Algorithm on PT. Koba Metal Indonesia - Sandi Kristianto; Yusuf Kurnia (Tech-E, 2018)
PT. Koba metal Indonesia. is one of roll-reforming cooperations who produce light-steel stuffs which is growing rapidly nowadays. One of the important thing in customer management is how a cooperation be able to preserve their customers. the effort of preserving customers becomes important for PT. Koba metal Indonesia. considering of plenty companies who commits at the same sector. To prevent the displacement of customers, knowing the potential group of customers is important, so that the company could preserve those potential customers by giving excellent service, etc. the implication of data mining could assist the company to analize the received data from sales transaction to gain potential customers data. Therefore, a designed application which could implement the data mining for choosing potential customers by clustering and algorithm K-means method is arranged. Then, the information performes with groups who is categorized into potential customers. Besides, rapminder application is also used to examine the data’s accuracy of this built application design. Hereinafter, this application design is expected to assist companies to choose their potential customers and preserve them to advance their business.