IMPLEMENTASI METODE K-MEANS UNTUK PENGELOMPOKAN TOPIK KARYA ILMIAH (TUGAS AKHIR) PADA PRODI TEKNIK KOMPUTER POLITEKNIK BISNIS INDONESIA
DOI:
https://doi.org/10.61722/jssr.v2i5.2743Keywords:
K-Means Clustering, RapidMiner Accuracy, Robotics FieldAbstract
This research aims to overcome the problems faced by final year students of the Indonesian Business Polytechnic, especially the Computer Engineering Study Program. In this study, the implementation process of the K-Means Method that can be applied on the campus of the Indonesian Business Polytechnic, especially the Computer Engineering study program, is carried out to group final year students in taking the topic of the final project scientific paper based on their abilities in the field of courses taken. Using the K-means Method, the process of grouping final year students is carried out by utilizing course value data from the mapping of courses in the field of robotics, networks and artificial intelligence. The grouping is adjusted to the ability of students with student scores that will be used as a benchmark for grouping. The results of the rapidminer application test have the highest accuracy value of 93% because the percentage of conformity is close to the manual K-means calculation compared to other applications. The results of the cluster for the first cluster as many as 13 students were directed to take the topic of scientific work (final project) Artificial Intelligence, the second cluster as many as 12 students were directed to take the topic of Networking, and the third cluster as many as 5 students were directed to take the topic of robotics.
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