<![CDATA[The lack of intereset in audio and video engineering competencies at SMK Muhammadiyah 9 Medan City causes the minimum number of students in the competence. Therefore, the school needs additional information as a tool to assist them in making a policy to continue or terminate the competency. By utilizing the Artificial Neural Network (ANN) approach, the researcher intends to build a student interest classification model based on student psychological datasets that can be used as a tool in analyzing student interest in audio and video engineering competencies. The classification model was built using 115 data divided into 92 training data and 23 testing data. Where the data will be transformed into binary numbers (1 and 0) in order to perform algorithm properly. The results of this study show that the model can classify student interest very well into the class labels "interested" and "not interested" as evidenced by the accuracy value of 98.9% on training data and 95.65% on testing data.]]>
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