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Implementasi Data Mining untuk Klasifikasi dan Pemerataan Guru pada Sekolah di Tangerang Eko Sutono; Anig Astofa
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 4 No 08 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

Problems in education is the lack of teachers, the teachers are not in accordance with the educational background (mismatch), low qualifications, competence disparities and uneven distribution of teachers. This study aims to (1) design a model of classification algorithms equity needs of teachers by using nearest neighbor algorithm (2) To design a classification algorithm model distribution needs of teachers by using algorithm C4.5 (3) compare the accuracy of the model and algorithm nearest neighbor algorithm C4.5 equity requirement for teachers. This study aims to (1) design a model of classification algorithms of equity needs of teachers by using nearest neighbor algorithm (2) To design a classification algorithm models the distribution needs of teachers by using algorithm C4.5 (3) compare the accuracy of the models and nearest neighbor algorithm C4.5 algorithm equity requirement for teachers. The results of this study is the information in the form of pattern classification state whether teachers need more, or less enough of nearest neighbor algorithm and C4.5 algorithms. Nearest neighbor algorithm accuracy rate reaches 72% and the accuracy rate reaches 83%.