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All Journal Jurnal Pilar Sains JSI: Jurnal Sistem Informasi (E-Journal) Jurnas Nasional Teknologi dan Sistem Informasi Annual Research Seminar RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Jurnal Komputer Terapan BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Nasional Komputasi dan Teknologi Informasi Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Jurnal Informasi dan Teknologi Jurnal Pengabdian Masyarakat Multidisiplin Journal of Ocean, Mechanical and Aerospace -science and engineering- (JOMAse) Alkhidmah: Jurnal Pengabdian dan Kemitraan Masyarakat
Roni Salambue
Program Studi Sistem Informasi, Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Riau
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Journal : Jurnal Informasi dan Teknologi

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Akurasi dalam Mengidentifikasi Citra Anggrek Menggunakan Backpropagation Artificial Neural Network Ardia Ovidius; Gunadi Widi Nurcahyo; Sumijan; Roni Salambue
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i3.115

Abstract

Orchids are ornamental flower plants in the Family Orchidaceae whose habitat is spread over almost all continents in the world, except Antarctica. There are so many orchid enthusiasts in Indonesia and this fact made orchids a promising commodity for ornamental plant cultivator. With a variety of orchid species that reach more than 25,000 species, the identification of orchid species becomes a little complicated for orchid lovers. The purpose of this study was to determine the accuracy level of orchid species identification through image recognition so that it can be used as a reference in determining the feasibility of this method. This study used 120 images of orchids in 6 species. The image of the orchid was obtained by shooting at several locations using the camera. The photo is then processed using image processing software by cropping and resizing to speed up computing time during network training. Furthermore, MatLab software is used to perform the feature extraction process in the form of color feature data and moment invariants. Data from feature extraction is used as input for training artificial neural networks using the Back Propagation method. Calculation of the level of accuracy done by testing the network using the test data that has been provided. The trial results show that 26 of 30 were successfully recognized so that the accuracy rate can be calculated, namely 86.7%. An accuracy rate of 86.7% can be considered feasible and can be used as a basis for consideration of using this tested method as the right method for identifying orchids through images.
Co-Authors Ahriyati Ahriyati Aidil Fitriansyah Al Aminuddin Anna Kaswari Annisa Devia Rahman Ardia Ovidius Arisandi, Diki Benny Putra Bunga Ariski Cinta Fitria Dedes Nawati Dodi Sofyan Arief Edy Fitra Elfizar Elfizar Elvia Budianita Elvia Budianita Evan Albert Hubertus Samosir Evfi Mahdiyah Fadhilah Syafria Fadhilah Syafria Fara Pricyla Fatayat Felix Dwi Artha Pakpahan Gunadi Widi Nurcahyo Habibi Al Rasyid Harpizon Herman Herman Herol Govand Nesvagan Sigalingging Ibnu Afdhal Inggyu Muria Br. Hasibuan Ismi Sifa Adila Iwan Iskandar Iwan Iskandar M Abdullah Minarni Minarni Muhammad Izzudin Muhammad Yusuf Alen Musdalifah Musdalifah Nanda Nur Fitriadi Nurdin Nurdin Rahmad Kurniawan Rangga Putra Pratama Salamun Salamun Silvia Agusti Sri Nurhidayati Sukamto, Sukamto Sukri Sukri Sumijan Valentina Br. Pakpahan Yanti Andriyani Zikri Alhadi