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All Journal Jurnal Ilmu dan Teknologi Hasil Ternak Jurnal Ilmu-Ilmu Peternakan (Indonesian Journal of Animal Science) Journal of Innovation and Applied Technology Jurnal Teknologi Pertanian Journal of Mechanical Engineering Science and Technology Jurnal Ilmiah Rekayasa Pertanian dan Biosistem Animal Production : Indonesian Journal of Animal Production JURNAL ILMIAH PETERNAKAN TERPADU Anterior Jurnal Jurnal Infomedia JURNAL PENDIDIKAN TAMBUSAI JURNAL BUDIDAYA PERTANIAN CERMIN: Jurnal Penelitian INTEGRITAS : Jurnal Pengabdian Asatiza: Jurnal Pendidikan Quantum Teknika Jurnal Nasional Holistic Science Jurnal Teknologi Hasil Peternakan Journal on Research and Review of Educational Innovation Jurnal Pertanian Kepulauan Journal of Science and Education Research Journal of Agriprecision & Social Impact Jurnal Mitra Dedikasi Masyarakat
Firman Jaya
Departemen Teknologi Hasil Ternak, Fakultas Peternakan, Universitas Brawijaya
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Journal : Anterior Jurnal

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Algoritma Deep Learning Untuk Pengenalan Gambar Jenis Daun: Deep Learning Algorithm for Leaf Type Image Recognition Azizah, Azizah; Nuswantoro, Setio Ardy; Jaya, Firman; Razaqi, Rahmat Shofan; Ansori, Ansori
Anterior Jurnal Vol. 23 No. 3 (2024): Anterior Jurnal
Publisher : ​Institute for Research and Community Services Universitas Muhammadiyah Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33084/anterior.v23i3.8199

Abstract

Image processing is a branch of informatics that deals with transforming one image into another using certain techniques. Deep learning algorithms have become one of the effective approaches to solving this problem. In this paper, we propose a deep learning algorithm that uses Convolutional Neural Networks (CNN) architecture to recognize leaf types based on a given leaf image. We outline the main steps in model development, including data pre-processing, CNN architecture selection, and model training. The experimental results show that the proposed deep learning algorithm can achieve a high level of accuracy in leaf-type image recognition. In this study, the CNN method is used to identify and classify objects in digital images, specifically leaves. The dataset used consists of 33 leaf classes, with a division of 16,500 data for training, 3,300 for validation, and 1,650 for testing. The training and validation processes were carried out in as many as 150 epochs, which resulted in the highest accuracy of 94% with the lowest loss of 0.28. While in the testing process, the accuracy value obtained reached 84%. The researched method, which integrates CNN with data augmentation and transfer learning, demonstrated superior performance with an accuracy of 94% in leaf type recognition. This outperforms other methods that rely solely on traditional CNN or do not utilize augmentation and transfer learning, which generally achieve lower accuracy rates. The combination of these techniques enables more robust feature extraction and better generalization, leading to more accurate and reliable classification results compared to other approaches.
Co-Authors Abdul Azis Abrori, Zainol Afia, Nur Agus Susilo Agus Susilo Agustini, Dini AHMAD FAISOL Akhadiyah Afrila Akhiroh, Puji Amalia, Alvina Wahyu Aminah, Sukma Ayu Nur Anang Lastriyanto Aris Sri Widati As'ad, As'ad Asep Awaludin Prihanto Astri Wulandari Azizah Azizah Azkarahman, Aldyon Restu Bahrun, Esthalia Kustin Pasole Dari, Astin Dedes Amertaningtyas Dewi Masyithoh Dewi Masyithoh Dewi, Siti Karunia Dicky Tri Utama Didik Kusumahadi Djalal Rosyidi Dyan Yuliana edy susanto Erwan Erwan Erwan Erwan, Erwan Fadia, Virotun Nisaul Febiyanto, Romy Febriyanti, Anis firmansah, septian Fitriatus Sholehah Handoyo, Mahendra Agus HASANAH, KHOLIFATUL Heldy Oktavia, Heldy Heli Tistiana Hendriansyah, Irfan Herly Evanuarini Herman Felani, Herman Ilma Mahdiana Imam Thohari Imam Thohari Imam Thohari Irawan, Dwi Citra Jamilah Jamilah Jati Batoro Jati Batoro Jati Batoro Khotibul Umam Al Awwaly Kosman, Kosman Kusumastuti, Anie Eka La Choviya Hawa Lamerkabel, J. S. A. Lilik Eka Radiati Lusiana Tulhusnah Mahalli, Mahalli Masauna, Esther D Masyithoh, Dewi Maulida, Yuni Miftahus Surur, Miftahus Mochamad Junus Mochammad Junus Mochammad Yunus, Mochammad Mohammad Rizal Hidayat Muawanah, Kholisatul Mustakim Mustakim Nadya Arera Ritma Ajeng Parlan Pepy Ade Merlina Premy Puspitawati Rahayu Purwadi Purwadi Purwadi Purwadi Purwadi Purwadi Puryantoro P Puspitasari, Yesi R, Rahmat Shofan Razaki, Rahmat Shofan Razaqi, Rahmat Shofan Ria Dewi Andriani Rini Dwi Wahyuni Salam, Darus Saputra, Anggi Ferdianto Eka Sasongko Aji Wibowo Seituni, Siti Setio Ardy Nuswantoro Setyo Prayogi , Heni Solly Aryza Sonhaji, Imam Sonia, Ulfatus Sri Minarti Supriatin Supriatin, Supriatin Tilawati Tilawati Tri Eko Susilorini Ummi Kalsum Untari, Wiwik Sri Ustadi Ustadi Utami, Puteri Aulia Utuwaly, Imas D Victor G Siahaya Wahyu Novia Widodo Wardana, Rifkian Jorgi Wibowo, Sasongko Aji Wulandari Saepuloh