IMPLEMENTASI ALGORITMA K-MEANS UNTUK PEMETAAN PRESTASI AKADEMIK SISWA DISEKOLAH DASAR TERANG BAGI BANGSA PATI
Keywords:
Clustering, Data Mining, Grouping student achievement, K-MeansAbstract
In an educational institution, the academic quality of each school is measured based on the academic achievement of each student, both academic grades each semester and National Examination scores. Bright Elementary School for the Pati Nation is one of the schools that is in the city of Pati. As the number of student data continues to increase every year, the number of students data that students continue to increase so that there is a lot of data accumulation that has not been processed properly optimal. For this reason, this research is needed to explore new information and knowledge through the patterns formed from the accumulation of the data. Data mining can take important information from large databases that humans need. Data mining methods that commonly used to cluster, namely K-Means. The purpose of K-Means is grouping data by maximizing data similarity in one cluster and minimizing data similarity between clusters. By using the K-Means Clustering Algorithm Method, it is possible to determine grouping of high, medium and low student achievement. Attributes used in research This is 15 attributes and produces 3 clusters. Low cluster_0 there are 2 items, cluster_1 medium there are 6 items and high cluster_2 there are 13 items.References
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