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Imaning Dyah Larasati
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Prediksi Kelulusan Mahasiswa Berdasarkan Kinerja Akademik Menggunakan Metode Modified K-Nearest Neighbor (MK-NN) Imaning Dyah Larasati; Ahmad Afif Supianto; Muhammad Tanzil Furqon
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In the Brawijaya University FILKOM Informatics Engineering study program, the academic performance of students in terms of study period is still a problem. In FILKOM's academic database, there are student academic data. The data can be carried out data mining by predicting students' graduation in the 5th semester. K-NN is a good method for predicting graduation. However, there is a method that has better accuracy than K-NN has been found in other cases, that is MK-NN. Therefore, this study using M-NN method for predict students' graduation based on academic performance by testing includes testing the effect of k value, the number of training data and the composition of training data. Furthermore, comparing the accuracy produced by MK-NN and K-NN methods. The highest accuracy of testing the effect of the value of k is when k = 5, which is equal to 82%. The highest accuracy from testing the effect of number of training data and the composition of training data reached 85,25% and 84%. From the comparison of the accuracy of MK-NN and K-NN it was concluded that MK-NN produced better accuracy than K-NN.
Co-Authors Ahmad Afif Supianto Muhammad Tanzil Furqon