PENERAPAN JARINGAN SYARAF TIRUAN UNTUK PENENTUAN SALAK UNGGUL DENGAN MENGGUNAKAN METODE LEARNING VECTOR QUANTIZATION

Authors

  • Luth Fimawahib Universitas Pasir Pengaraian
  • Leony Lidya Universitas Pasundan
  • Gunadi Widi Nurcahyo Universitas Putra Indonesia “YPTK” Padang

Keywords:

Artificial Neural Network, Learning Vector Quantization, Snake Fruit, Tools Matlab.

Abstract

Rokan Hulu is one of district in Riau Province that cultivated Snake Fruit plant. Recently, the cultivation of this plant doesn’t conducted maximally because of the lack of farmer’s knowledge. The varieties of high quality Snake Fruit takes effect toward the productivity of Snake Fruit. Because of that, it needs evaluation in determining high quality Snake Fruit. Artificial Neural Network with Learning Vector Quantization in this research is used to train high quality Snake Fruit plant based on it’s class, namely High Quality I and High Quality II. The testing of this method is conducted by using Matlab in order to obtain classification accuracy level. This research uses 60 training dataset and 40 testing dataset of Snake Fruit plant. These data are obtained by using observation at Snake Fruit Plantation located in Desa Rambah Muda Kecamatan Rambah Hilir Kabupaten Rokan Hulu. The result of this research shows that the highest accuracy percentage of training and testing data are respectively 91.66% and 92.50%.

References

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Published

2019-07-27