<![CDATA[The PLN industrial class is a class that collaborates with PT. PLN Persero by including a curriculum in accordance with the competencies required by the industry. Students entering industrial classes must also be selected students. Therefore we need a system to classify students. The grouping of students at SMK Muhammadiyah 3 Surakarta is still manual, so the grouping process is not optimal and accurate.The purpose of this thesis is the creation of a class grouping application based on productive academic and attitude values using the Fuzzy C-Means method. And make it easier to do class grouping. Data collection methods include observation or data collection at SMK Muhammadiyah 3 Surakarta, interviews with the Head of the electrical power installation engineering (TITL) Skills Competency and literature studies taken from journals, books and also related research.This class grouping system is created using the Fuzzy C-Means method. After grouping the results obtained from 26 students, 21 students entered the industrial class and 5 students entered the regular class. The results of the validity test prove that the clustering is valid, as evidenced by the silhouette coefficient test where the value is 0.81 which indicates a strong structure.]]>
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