Sistem Informasi Pemetaan Pendidikan Menggunakan Algoritma Data Mining
Abstract: in this study to
identify the increase in educational services based on the quality of
non-formal education is an indicator, having tiered in terms of education,
non-formal education (training) to be one of the prerequisites in multiplying
the potential for self-development. Data mining algorithms is a basic k-means
clustering to put the object based on the average (Means) nearest cluster. Aims
to design mapping information system education with the k-means cluster.
Application k-means cluster is part of a non-hierarchical method, the mapping
system of education in 171 samples of data Isalam Students Association (HMI)
were tested in this study showed that the non-hierarchical method (k-means
cluster) has a good degree of accuracy because they specify the number of
clusters in advance. Education information system mapping is used to cluster
the data level, corresponding formal education and training has been followed.
Education information system mapping is used to cluster the data level,
corresponding formal education and training has been followed . The test
results have in me some real, the spread of the data in each cluster are
similar. At the time of the iteration process is not visible difference in the
results of the mapping study using the k-means cluster. Results of a cluster
centroid information models with variable 4 educated members include S1, S2,
has entered basic training cluster 0, educated S1, S2, S3 has entered basic
training cluster 1, S1 has educated basic training and training of incoming
intermediate cluster 2, educated S1 has entered basic training cluster 3. formal
education, education tiered seen in cluster 1 for non-formal education
(training) tiered education seen in cluster 2. Based the test results k-means
cluster.
Penulis: Olha Musa, Suhartono
Koe Jurnal: jptinformatikadd150245
