ANALISIS PROFIL AKADEMIK ALUMNI DENGAN MENGGUNAKAN METODE KLASTERISASI K-MEANS - Anggraini, Dewi; Wisnubhada, Irya; Mudjihartono, Paulus (Proceedings of KNASTIK, 2013)
Universities are currently required to have the ability to compete by utilizing all its resources. In addition to the resources of facilities, infrastructure, and human, data and information systems are some resources that can be used to improve the ability to compete. One of the elements that must be considered in the development of a college is to be able to compete data alumni academic. STIKOM Uyelindo Kupang have sufficient academic alumni data to be analyzed. With alumni academic data clustering, decision makers can identify the characteristics of alumni profiles. Characteristics of alumni profiles can then provide an overview and consideration of the development of university policies related to alumni. In this paper, k -means algorithm is used for the data mengklasterisasi academic graduates with the purpose of showing the characteristics of the profile information of alumni. Clustering results with 226 data from three study programs (S1/D3 informatics engineering and information systems S1), and with k = 3, the group acquired sufficient data points to a pattern of firm alumni profiles can support the decision.