The graduates of State Polytechnic of Semarang are not only the member of social community but also part of State Polytechnic of Semarang community who have academic knowledge and special skills. Based on the researcher observation the graduates of State Polytechnic of Semarang are not recorded, the management of State Polytechnic of Semarang has not provided a system that can facilitate the interaction between State Polytechnic of Semarang and graduates. In this thesis, the system for mapping the graduates distribution is aimed to measure the level of the graduates compliance skill with the competence area of their job. The method of KMeans Clustering is used for grouping the distribution of State Polytechnic of Semarang graduates. Grouping or clustering mechanism in this system is based on four variables. They are type of company, job classification, working area, and competency of study program. While the geographical position of graduates is used to filter the data when the users are searching the graduates location in a ce rtain province. In this research the cluster is divided into three, they are, cluster one: graduates have matching competence, cluster two: graduates have matching enough competence, and cluster three: graduates have no matching competence.
Keywords: Clustering; GIS ; K-Means
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Segmentation and distribution of watershed using K-Modes clustering algorithm and Davies-Bouldin index based on geographic information system (GIS)
Muhammad Farid Fahmi, Yoyon K. Suprapto, Wirawan. 2016 International Seminar on Application for Technology of Information and Communication (ISemantic), 2016. doi: 10.1109/ISEMANTIC.2016.7873844School zoning system using K-Means algorithm for high school students in Makassar City
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