Pengelompokan Tingkat Pengembangan Bakat pada Anak Menggunakan Metode Clustering
DOI:
https://doi.org/10.54066/jpsi.v2i3.2247Keywords:
Data Mining, K-Means Algorithm, Child TalentAbstract
Education is one measure of success or success in the knowledge/intelligence of students with their talents. Talent is an innate potential ability, which still needs to be honed and retrained so that it can become a capable ability, expertise and skills. Talent can be obtained from several ability tests that will be carried out so that children can find out what talents they have. MIS Mutia Rahma is a school that plays an important role in developing the talents of each of its students with various standards from the lowest to the highest. This school strives to maximize the potential of its students. Based on data obtained from 2010-2022, there are 1056 student talent development data. However, from this data it is not yet clear how the process of dividing groups and monitoring student talents is carried out. Therefore, an effective method is needed to process this data in order to classify the development of children's talents. The method that can be used to group data on children's talent development is the K-Means algorithm. Of the 20 data, there are 3 groups, namely group 1 has 7 data and group 2 has 11 data, and group 3 has 2 data with the most results obtained being cluster 2 with the group level of talent development in children aged (X) 8-10 years, who have the ability (Y) linguistic ability (KL), musical ability (KM), spatial ability (KS), kinesthetic ability (KK) & intrapersonal ability (KIP), the type of extracurricular (Z) that is developed in children is Football.
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