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Muhammad Siddik
STIKOM Pelita Indonesia Pekanbaru
Computer Science & IT

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PENENTUAN BIDANG KONSENTRASI TUGAS AKHIR MENGGUNAKAN METODE LEARNING VECTOR QUANTIZATION Muhammad Siddik
RJOCS (Riau Journal of Computer Science) Vol. 3 No. 1 (2017): Riau Journal of Computer Science
Publisher : RJOCS (Riau Journal of Computer Science)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (848.304 KB) | DOI: 10.30606/rjocs.v3i1.1402

Abstract

Sekolah Tinggi Ilmu Ekonomi (STIE) Pelita Indonesia Pekanbaru has obstacles in increasing its graduates annually, regarding the Final Project (TA) problem. Many of the methods used in making the final task make the students difficult in determining the theme of their final project. So in determining the field of concentration Final Project outside the courses that they take, causing the work of the End Task becomes constrained and even tend to hire others in solving it. Neural Networks Learning Vector Quantization (LVQ) method can be applied in classifying the field of concentration of the final task in accordance with the pattern of course grades taken. The results of training and testing conducted on the data train with a total of 44 dataset data for training data and 28 datasets for test data, learning on epoch to 1500, 2500 and 5000 and learning rate 0.01, 0.03 and 0.05 obtained the same data accuracy rate of 75 % with the correct amount of data in the classification process of 33 datasets and 11 datasets that do not match the target or class. As for the test data, the data accuracy level of 82.1429% with the correct amount of data 23 datasets and 5 datasets that are not in accordance with the target or class.
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