<![CDATA[Based on the initial assessment that the author did at SDN 70 KENDARI, the average student achievement at SDN 70 KENDARI was quite high. High learning outcomes are of course influenced by several factors, one of which is the teacher's ability factor. Teachers who have high abilities in managing learning, as in the case of using instructional media, of course, will make it easier for students to understand the subject matter presented, which directly results in high student achievement. Starting from the thoughts above, the principal wants to improve teacher competence in applying learning media through learning supervision. This research is a school action research (School Action Research). This research will be conducted at SDN 70 KENDARI. The research will be conducted in semester 2 of the 2022/2023 Academic Year. Data collection methods in this study are observation techniques, interviews and documentation. In the pre-cycle the researchers just observed how much the teacher's competence was in applying learning media and it turned out that the results were very low, namely getting an average score of only 6.4, meaning that the teacher's competence in applying learning media was not good. In view of the observation results, there was an increase in the average score from pre-cycle to cycle I, where the results of the average pre-cycle observation score only reached a score of 6.4 while in cycle I it reached 11.4, which means that the teacher's competence in applying learning media is good . Furthermore, in cycle II, the observation results reached a score of 15.8, meaning that the teacher's competence in applying learning media was very good. Supervision of learning at SDN 70 KENDARI can be done through observing and monitoring the school principal in supervising learning. From the results of the analysis it was found that, Supervision of learning is very effective for increasing teacher competence in applying learning media, because teachers have the opportunity to discuss together to study and solve problems based on conditions in the field, then can improve them or carry out follow-up in the next cycle automatically. continue if the problem is not resolved..]]>
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