PENGENALAN POLA BUNGA BERBASIS CITRA MENGGUNAKAN JARINGAN SARAF TIRUAN DENGAN ALGORITMA PERCEPTRON
DOI:
https://doi.org/10.23969/jp.v9i04.18128Keywords:
ANN, perceptron, flower patternAbstract
Flowers are transformations of buds, including stems and leaves, with shapes and colors adapted to the plant's functions. They also serve as sites for fertilization and pollination. Flowers come in various shapes and colors, with over 250,000 flowering plant species known and classified into 350 families. Therefore, employing technology for flower pattern recognition is crucial for enhancing accuracy and efficiency. One effective method involves using Artificial Neural Networks (ANN) in conjunction with the perceptron algorithm. This algorithm has proven effective in image-based pattern recognition due to its ability to learn complex and linear patterns from image data. This study explores the use of neural networks, specifically the perceptron method, in recognizing flower patterns. The test utilizes sunflower image samples, with the perceptron algorithm applied to produce accurate and effective data in flower pattern recognition.Downloads
References
Aprijani, D. A. (2013). APLIKASI JARINGAN SYARAF TIRUAN UNTUK MENGENALI TULISAN TANGAN HURUF A , B , C , DAN D PADA JAWABAN SOAL PILIHAN GANDA ( Studi Eksplorasi Pengembangan Pengolahan Lembar Jawaban Ujian Soal Pilihan Ganda di Universitas Terbuka ). Jurnal Matematika, 2(2001).
Arlis, S., Ekajaya, D. S., Studi, P., Informasi, S., Ilmu, F., Studi, P., Informatika, T., Ilmu, F., Tiruan, J. S., Sutikno, S., & Musthof, U. (2018). Pola Penentuan Status Peminjaman Dengan. 619–623.
Dijaya. (2023). Buku Ajar Pengolahan Citra Digital. In Umsida Press.
Fitryadi, K. (2018). Pengenalan Jenis Golongan Darah Menggunakan Jaringan Syaraf Tiruan Perceptron. Jurnal Masyarakat Informatika, 7(1).
Muchtar. (2015). Penggabungan fitur dimensi fraktal dan lacunarity untuk klasifikasi daun. I. In Institut Teknologi Sepuluh Nopember, Surabaya .
Mulia, M. R., Kaswar, A. B., Andayani, D. D., Sadri, A., Makassar, U. N., & Korespondensi, P. (2024). CLASSIFICATION OF THE NUTRITIONAL CONTENT OF BANANAS BASED ON TEXTURE AND COLOR FEATURES IN THE LAB AND USING ARTIFICIAL. Jurnal Teknologi Informasi Dan Ilmu Komputer, 11(3), 507–518.
Perwati, I. G., Suarna, N., & Suprapti, T. (2024). ANALISIS KLASIFIKASI GAMBAR BUNGA LILY MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK ( CNN ) DALAM PENGOLAHAN CITRA. JATI (Jurnal Mahasiswa Teknik Informatika), 8(3), 2908–2915.
Puspita. (2019). Ampuhnya Tanaman Hias Bagi Kesehatan dan Kecantikan. In LAKSANA.
Putra, R. R., & Antony, F. (2018). Sistem Computer Vision Pengenalan Pola Angka dan Operator Matematika Pada Permainan Kartu Angka Berbasis Jaringan Syaraf Tiruan Perceptron. JURNAL ILMIAH INFORMATIKA GLOBAL, 09(01).
Supriatna. (2008). Melestarikan Alam Indonesia. In Yayasan Obor Indonesia.
Utnasari, I. (2018). PENERAPAN JARINGAN SYARAF TIRUAN PADA PENGENALAN BACKPROPAGATION Intan Utnasari. Computer Based Information System Journal, 01(2), 7–11.
Yani, D. R. (2020). Penerapan Jaringan Syaraf Tiruan Dalam Pengenalan Huruf Aksara Suku Karo dengan Metode Perceptron. Journal of Information System Research (JOSH), 1(3), 109–114.
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