There are several ways to assess the best teacher in determining the potential teacher. This aims to encourage teachers to excel and see the motivation, dedication, and loyalty of teachers, as well as see the professionalism of a teacher in technological advancements based on 4.0. From the research conducted in determining the best teacher, there are problems, including in the selection of the best teacher, the principal tends to choose based on observations made only by the principal himself and does not pay attention to the criteria and indicators of assessment in the form of professional, personality and social which makes the teachers less than optimal in their work. Therefore we need a system to solve some of the problems that occur. A system was built to overcome the problem in the form of a decision support system. A decision support system is a system aimed at management in helping to make the right decisions. The method used is K-Nearest Neighbor, which is a method for making decisions using supervised learning where the results of the new input data are classified based on the closest in the value data. Calculations were carried out in 2020 and 2021. The total value of data in the previous year was 70 lines of data. If it is further detailed, the data used is 1190 value data. The assessment prediction data used is teacher data in 2021, as many as 37 lines of data. The k-NN algorithm uses the value of k to determine the number of nearest neighbors whose status will be calculated.
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