APLIKASI PENENTUAN GOLONGAN DARAH MANUSIA DENGAN METODE SEED REGION GROWING DAN SELF ORGANIZING MAPS

  • David Wewo(1)
    Universitas Nusa Cendana
  • Adriana Fanggidae(2*)
    Universitas Nusa Cendana
  • Kornelis Letelay(3)
    Universitas Nusa Cendana
  • (*) Corresponding Author

Abstrak

The blood type of human are divided by four group wich is blood type A, B, O & AB. Artificial Neuron Network can help the identify process for blood type. Self organizing maps is a part of arrtificial neuron network who has function for data training and data clasification. The image data are using by blood clotting and obtained after spilled blood sample with the reagent. The real data image are converted into grayscale image, For taking the characteristic are doing by converted real image to image biner with the treshold more than 80 and smaller than 150, image are taken as much as 12 image of clotted blood and 12 image blood wich does not clot, and the next step will do the training process using self organizing maps. The first testing data are doing by the same test data and same with training data too and the result 100%. The second testing data is doing by 12 blood image test data wich is not the same as data training and the result 83.33%.

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Referensi

[1] Aryadhi S., 2008, Identifikasi Golongan Darah Manusia Dengan Teknik Pengolahan Citra Menggunakan Metode Jaringan Syaraf Tiruan, Skripsi, Jurusan Teknik Elektro Fakultas Teknik Universitas Indonesia. Depok.
[2] Kusumadewi S, 2003, Artificial Intelligence (Teknik dan Aplikasinya), Graha Ilmu, Yogyakarta
[3] Pranada, N., 2013, Pemanfaatan Seed Region Growing Segmentation dan Momentum Backpropagation Neural Network untuk Klasifikasi Jenis Sel Darah Putih, Universitas Sebelas Maret. Surakarta.
[4] Prawirohartono, S. 1995. Sains Biologi. Bumi Aksara. Jakarta
[5] Sari.W.Z., 2010, Pengenalan Pola Golongan Darah Menggunakan Jaringan Syaraf Tiruan Back Propagation, Skripsi, Jurusan Teknik Informatika Fakultas Sains dan Teknik Universitas Islam Negeri. Malang.
[6] Siahaan M., 2009, Implementasi Segmentasi Citra Menggunakan Metode Graph Yang Efisien, Skripsi, Jurusan Matematika Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Sumatera Utara. Medan.

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2018-03-31
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