<![CDATA[The world of education is in a transitional period where there are many changes and adjustments in all aspects of the education sector, especially for the quality of teachers and teaching staff and the distribution of teachers and teaching staff is still not evenly distributed. Data Mining Techniques. And the K-Nearest Neighbor Algorithm can classify some of the problems that teachers have. The data used for classification include the educational background of teachers, the needs of teachers in each school, data on the number of teachers and data on the number of schools. The results of the calculation of 2000 data resulted in the classification of each category of teachers, namely civil servant teachers, PPPK teachers, honorary teachers, and honorary teachers which were not linear between educational background and subjects taught. For PNS teachers who match the educational background, 30%. First aid teachers are in accordance with 20% education, for honorary teachers who are in accordance with the educational background of 10% and 40% for honorary teachers who are not in accordance with the educational background and subjects taught.]]>
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