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Abstract
ABSTRAK
Penelitian ini melakukan perancangan aplikasi pengenalan gangguan ginjal dini melalui citra digital iris mata menggunakan metode convolutional neural network (CNN) dengan antarmuka Raspberry Pi 3 model B+. Hasil akurasi terbaik yang diperoleh dengan memvariasikan banyak epoch, nilai learning rate, ukuran kernel, komposisi database, dan fungsi pooling layer adalah 94% pada saat epoch 12, 92% pada nilai 0,0001, 95% pada ukuran 3x3, 95% pada komposisi 100 train dan 50 validation, 90% menggunakan fungsi max pooling.
Kata kunci: gangguan ginjal, iridology, convolutional neural network, raspberry pi.
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References
- DAFTAR PUSTAKA
- Aisara, Sitifa, dkk. 2018. Gambaran Klinis Penderita Penyakit Ginjal Kronik yang Menjalani Hemodialisis di RSUP Dr. M. Djamil Padang. Padang: Universitas Andalas.
- Fresenius Medical Care. 2012. ESRD Patients in 2012: A Global Perspective.
- Lathifah, Annis Umi. 2016. Faktor Risiko Kejadian Gagal Ginjal Kronik Pada Usia Dewasa Muda di RSUD dr. Moewardi. Skripsi. Surakarta: Universitas Muhammadiyah Surakarta.
- Trihono. 2013. Riset Kesehatan Dasar. Jakarta: Badan Penelitian dan Pengembangan Kesehatan Kementrian Kesehatan RI.
- Jensen, B. 1982. What is Iridology. Ben Jensen Enterprise Publishers. California.
- Setiawan, Bambang. 2009. Identifikasi Iris Mata Menggunakan Metode Hidden Markov Model. Tesis. Depok: Universitas Indonesia.
- Nurhikmat, Triano. 2018. Implementasi Deep Learning Untuk Image Classification Menggunakan Algoritma Convolutonal Neural Network (CNN) Pada Citra Wayang Golek. Skripsi. Yogyakarta: Universitas Islam Indonesia.
- Danukusumo, Kevin Pudi. 2017. Implementasi Deep Learning Menggunakan Convolutional Neural Network untuk Klasifikasi Citra Candi Berbasis GPU. Skripsi. Yogyakarta: Universitas Atma Jaya Yogyakarta.
- Srivastava, N., Hinton, G, and Kriszhevsky, A. (2014). Dropout: A Simple Way to Prevent Neural Network. Journal Conference Learning Research, 19291958.
References
DAFTAR PUSTAKA
Aisara, Sitifa, dkk. 2018. Gambaran Klinis Penderita Penyakit Ginjal Kronik yang Menjalani Hemodialisis di RSUP Dr. M. Djamil Padang. Padang: Universitas Andalas.
Fresenius Medical Care. 2012. ESRD Patients in 2012: A Global Perspective.
Lathifah, Annis Umi. 2016. Faktor Risiko Kejadian Gagal Ginjal Kronik Pada Usia Dewasa Muda di RSUD dr. Moewardi. Skripsi. Surakarta: Universitas Muhammadiyah Surakarta.
Trihono. 2013. Riset Kesehatan Dasar. Jakarta: Badan Penelitian dan Pengembangan Kesehatan Kementrian Kesehatan RI.
Jensen, B. 1982. What is Iridology. Ben Jensen Enterprise Publishers. California.
Setiawan, Bambang. 2009. Identifikasi Iris Mata Menggunakan Metode Hidden Markov Model. Tesis. Depok: Universitas Indonesia.
Nurhikmat, Triano. 2018. Implementasi Deep Learning Untuk Image Classification Menggunakan Algoritma Convolutonal Neural Network (CNN) Pada Citra Wayang Golek. Skripsi. Yogyakarta: Universitas Islam Indonesia.
Danukusumo, Kevin Pudi. 2017. Implementasi Deep Learning Menggunakan Convolutional Neural Network untuk Klasifikasi Citra Candi Berbasis GPU. Skripsi. Yogyakarta: Universitas Atma Jaya Yogyakarta.
Srivastava, N., Hinton, G, and Kriszhevsky, A. (2014). Dropout: A Simple Way to Prevent Neural Network. Journal Conference Learning Research, 19291958.