Aplikasi Klasifikasi Peminatan Studi Lanjut Dengan Menggunakan Metode K-Nearest Neighbor

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Claudio L. F. Untu
Debby Paseru
Thomas C. Suwanto


Specialization in advanced studies (Strata-2) is the ideal or goal of some people who want to deepen their knowledge and skills according to their interests and talents. However, many undergraduate graduates are still confused about what field of study to pursue. Students only follow friends in selecting courses each semester when taking undergraduate education. Choosing the wrong major that does not match your interests and talents results in a mismatch between work and talent. The K-Nearest Neighbor (KNN) method is a method that uses a supervised algorithm where the results of the new query instance are classified based on the majority of the class labels in the KNN. The purpose of the KNN algorithm is to classify new objects based on attributes and training data. Based on the tests that have been carried out, determining the classification of further study specialization using the KNN method with a value of k = 5 and training data totaling 148 actual data, with an accuracy level of 86.486%, a recall of 86.486% and an error rate of 13.513%.

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