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Penerapan K-Nearest Neighbour dalam Penerimaan Peserta Didik dengan Sistem Zonasi

Denni Kurniawan orcid scopus  -  Universitas Budi Luhur, Indonesia
*Ade Saputra  -  Universitas Budi Luhur, Indonesia
Open Access Copyright (c) 2019 JSINBIS (Jurnal Sistem Informasi Bisnis)

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Abstract
Admission of new students is a routine activity at the beginning of each new meeting year in all formal educational institutions. At the moment the acceptance of new students uses the zoning system and has been regulated by Permendikbud No. 20 in 2019. This zoning system will accept students where their residence enters through the user area with the school environment. With this Permendikbud the government hopes that there will be an evenness in the quality of education in all schools, so that schools will no longer get the title of superior and non-superior schools. But in a system, the zoning improves anxieties in the school environment. This research supports to help the participating school students will be accepted in accordance with the provisions of the Ministry of Education and Culture. In overcoming problems that arise in the school environment there needs to be a system that can overcome that problem. In this study using the K-Nearest Neighbor (K-NN) method. Where the K-NN method will do the classification of new learners' residence with the school. In determining the classification using the K-NN method used for zoning and non-zoning areas, it is seen based on the closest K value. In finding the optimal value in this study using the Rapidminer application. The optimal high-level test results at K 5 where the value of this K is 83.36%

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Keywords: Data Mining, K-NN, Rapidminer, Zonasi

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