Pengaruh HSV Pada Pengolahan Citra Untuk Kematangan Buah Cabai
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Arifiyanto Hadinegoro
*
Universitas Amikom, Yogyakarta,
Indonesia
- Dicky Andhika Rizaldilhi Universitas Amikom, Yogyakarta, Indonesia (*) Corresponding Author
Abstract
Image or image recognition has quite complex stages so that the computer is able to recognize what objects to identify, there are several stages used in the image processing process, image extraction data input and image classification, this study will examine the extent to which the algorithm for extraction have an influence on the final classification results. This study uses the image of chili as a test material and the results of the test are the introduction of chili with 4 levels, ripe, half cooked, raw and rotten. This study also uses tools to perform the image recognition process. The image recognition method used in this study is Hue Saturation Value (HSV) Gray Level Co-occurrence Matrix (GLCM) and Learning Vector Quantization (LVQ3) for classification, in the process it will be tested. With 2 image recognition scenarios, the first method uses GLCM and LVQ3, the second scenario uses HSV GLCM and LVQ3. The results of this study are to see how much influence HSV has on the digital image recognition process of chili, the extraction results using GLCM extraction LVQ3 classification is 59.58%, and the results of LVQ3 classification using HSV and GLCM extraction yields 93.58%. In conclusion, the HSV extraction method provides an additional 34% accuracy compared to using only GLCM as the extraction method
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References
y. p. wiharja dan A. Harjoko, “Pemrosesan Citra Digital untuk Klasifikasi Mutu Buah Pisang Menggunakan Jaringan Saraf Tiruan,” IJEIS, pp. 57-58, 2014.
A. Jakarta, S. Mu'minah, D. Riana dan S. Hadianti, “Klasifikasi Varietas Buah Kiwi dengan Metode Convolutional Neural Networks Menggunakan Keras,” Jurnal MEdia Informatika Budidarma, pp. 1309-1315, 2021.
J. A. Pratama, “IMPLEMENTASI K-NEAREST NEIGHBOUR UNTUK KLASIFIKASI KUALITAS TEMBAKAU MENGGUNAKAN DIGITAL IMAGE PROCESSING BERBASIS ANDROID,” Universitas jember , Jember, 2015.
D. T. Hermanto, S. Megira, D. Ninosari dan Kusrini, “IDENTIFIKASI TINGKAT KEMATANGAN BUAH STRAWBERRY MENGGUNAKAN GRAY LEVEL CO-OCCURANCE MATRIX (GLCM) DAN LAPLACIAN FILTER,” dalam Seminar Nasional Teknologi Informasi dan Multimedia 2018, Yogyakarta, 2018.
D. P. Pamungkas, “Ekstraksi Citra menggunakan Metode GLCM dan KNN untuk Indentifikasi Jenis Anggrek (Orchidaceae),” Innovation in Research of Informatics (INNOVATICS), pp. 51-56, 2019.
F. M. D. Febrianan, R. R. Isnanto dan A. A. Zahra, “PENGENALAN GARIS UTAMA TELAPAK TANGAN DENGAN EKSTRAKSI CIRI MATRIKS KOOKURENSI ARAS KEABUAN MENGGUNAKAN JARAK EUCLIDEAN,” Transient: Jurnal Ilmiah Teknik Elektro, p. 511, 2015.
Ryansyah, “Identifikasi Tingkatan Warna Pada Kopi Roasting Menggunakan Metode HSV Berbasis Mobile,” TIN: Terapan Informatika Nusantara, pp. 520-526, 2021.
W. f. Roshandri, E. Utami dan A. B. Prasetio, “Segmentasi Luka Diabetes Menggunakan Masking Contour Image Processing,” Jurnal SISFOTRNIKA, pp. 111-123, 2021.
F. Liantoni dan F. N. Annisa, “FUZZY K-NEAREST NEIGHBOR PADA KLASIFIKASI KEMATANGAN CABAI BERDASARKAN FITUR HSV CITRA,” JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika), pp. 101-108, 2018.
R. Hamidi, M. T. Furqon dan b. Rahayudi, “Implementasi Learning Vector Quantization (LVQ) untuk Klasifikasi Kulaitas Air Sungai,” Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, pp. 1758-1763, 2017.
U. Sudibyo, D. P. Kusumaningrum, E. H. Rachmawanto dan C. A. Sari, “OPTIMASI ALGORITMA LEARNING VECTOR QUANTIZATION (LVQ) DALAM PENGKLASIFIKASIAN CITRA DAGING SAPI DAN DAGING BABI BERBASIS GLCM DAN HSV,” SIMETRIS, vol. 9, no. 1, pp. 1-10, April 2018.
M. Sarimin, M. Bettiza , N. Hayaty dan S. Nugraha, “Implementasi HSV dan GLCM untuk Deteksi Kesegaran Ikan Bawal menggunakan Radial Basis Function Berbasis android,” Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan, pp. 1-7, 2019.
F. M. Putra dan F. Syarifa, “Penerapan Learning Vector Quantization 3 (LVQ3) untuk Mengidentifikasi Citra Darah Acute Lymphoblastic Leukemia (ALL) dan Acute Myeloid Leukemia (AML),” CoreIT, pp. 27-33, 2018.
M. A. Abilisa, R. Magdalena dan s. Sa'idah, “IDENTIFIKASI JENIS KULIT MANUSIA MENGGUNAKAN METODE GLCM DAN LVQ BERBASIS ANDROID,” dalam e-Proceeding of Engineering, bandung, 2021.
D. Wandi, Fauziyah dan N. Hayati, “Deteksi Kelayuan Pada Bunga Mawar dengan Metode Transformasi Ruang Warna Hue Saturation Intensity (HSI) dan Hue Saturation Value (HSV),” JURNAL MEDIA INFORMATIKA BUDIDARMA, pp. 308-316, 2021.
C. Chotimah, A. Sofyan dan H. Tuti, “Respon Beberapa Pupuk Bokashi Padat Terhadap Hasil Produksi Tanaman Cabai Rawit Hiyung,” AGROEKOTEK VIEW, pp. 7- 15, 2020.
D. Putra, Pengolahan Citra Digital, Yogyakarta: Andi Offset, 2010.
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