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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmu Lingkungan Kopasta: Jurnal Program Studi Bimbingan Konseling Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Kesehatan Komunitas JOURNAL OF APPLIED INFORMATICS AND COMPUTING PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Computer Based Information System Journal JURIKOM (Jurnal Riset Komputer) Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal JIK- JURNAL ILMU KESEHATAN Journal of Education, Humaniora and Social Sciences (JEHSS) Building of Informatics, Technology and Science Surya Medika: Jurnal Ilmiah Ilmu Keperawatan dan Ilmu Kesehatan Masyarakat KAIBON ABHINAYA : JURNAL PENGABDIAN MASYARAKAT Prosiding National Conference for Community Service Project Abdimas Galuh : Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika (JUTIF) Jurnal Kesehatan Tambusai Jurnal Pengabdian Kesehatan Komunitas (Journal Of Community Health Service) Journal of Indonesian Management Jurnal Puan Indonesia Journal of Education Technology Information Social Sciences and Health Student Scientific Creativity Journal Indonesian Research Journal on Education Jurnal Desain dan Analisis Teknologi Jurnal Keperawatan Jurnal Ilmu Kedokteran dan Kesehatan Indonesia Jurnal Keperawatan Profesional Polygon: Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Masyarakat Mandiri: Jurnal Pengabdian Dan Pembangunan Lokal Computer & Science Industrial Engineering Journal Prosiding Seminar Nasional Ilmu Sosial dan Teknologi (SNISTEK) Jurnal Ilmu Kedokteran dan Kesehatan Indonesia
Nopriadi Nopriadi
Universitas Putera Batam
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Journal : Building of Informatics, Technology and Science

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Penerapan Deep Learning pada Pengolahan Data Citra dan Klasifikasi Udang Vaname Menggunakan Algoritma Convolutional Neural Network Astiti, Sarah; Nopriadi, Nopriadi; Novrian, Willi; Putra, Yusran Panca
Building of Informatics, Technology and Science (BITS) Vol 6 No 1 (2024): June 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i1.5418

Abstract

Deep learning-based shrimp image processing has become a rapidly growing research field in recent years. This technology aims to increase efficiency and accuracy in various applications related to the fishing and aquaculture industry, such as monitoring shrimp health, disease detection, species classification, and assessing the quality and quantity of harvested crops. Based on observations to date, fish sellers and buyers in the market have difficulty distinguishing vaname shrimp cultivated in tarpaulin ponds and earthen ponds. This research aims to apply deep learning techniques to determine the classification of Litopenaeus vannamei shrimp cultivation results in earthen ponds and tarpaulin ponds. To facilitate this research, the author uses a classification method by applying two Convolutional Neural Network (CNN) architectures, namely Visual Geometry Group-16 (VGG-16) and Residual Network-50 (ResNet-50). The dataset used in this research is 2,080 images per class of vannamei shrimp from two types of shrimp ponds. The results of this research are learning rates of 0.001 and 0.0001 on the Stochastic Gradient Descent (SGD) and Adaptive Moment Estimation (ADAM) optimizer to evaluate their effectiveness in model training. The VGG-16 and ResNet-50 models were trained with a learning rate parameter of 0.0001, taking advantage of the flexibility and reasonable control provided by the SGD optimizer. Lower learning rate values ​​were chosen to prevent overfitting and increase training stability. Model evaluation showed promising results, with both architectures achieving 100% accuracy in classifying vannamei shrimp from ground and tarpaulin ponds. The conclusion of this research is to highlight the superiority of using SGD with a learning rate of 0.0001 versus 0.001 on both architectures, then the significant impact of optimizer selection and learning rate on the effectiveness of model training in image classification tasks
Co-Authors Al Mujahid, Abdaur Rusdi Alvendo Wahyu Aranski Amir, Yufitriana Amrizal Amrizal Amrizal Amrizal Ananda, Tiara Annisa Annisa Aqila, Jihan Azzahra Nasha Aras Mulyadi Arianto, Tomi Arnomo, Sasa Ani Asra, Zahra ASRIL ASRIL aziz, ari rahmat Azwanti, Nurul Br Munthe, Cristina Lasmaria Damanik, Senna Rohdelima Danuri Danuri, Danuri Dedi Kurniawan Dennis, Nigel Didi Kurniawan Dilaruri, Ade Dinda Bucira Almaa Elisa, Erlin Ellbert Hutabri Endro Basuki Faisal Faisal Fajrin, Alfannisa Annurrullah Fazira, Shella Febriana - Sabrian ferdinan, fander Ginting, Asher Azriel Harman, Rika Hellena Deli Herfianti, Meiffa Herlina Herlina Herly Dwiyanto, Herly Dwiyanto Hernita, Rifa Ikhsyan, Muhammad Nur Kelvin Korino, Korino Leonita, Emy Leonita, Emy leonita Lumbantobing, Harjono Malau, Yohanes Gervasius Vandher Yovi Maulana Zein, Rhendiya Mega Rahmawati, Mega MOHD. Bintan Kurnia Putra Mualimin MUHAMMAD RIZAL Mukhlas_Ikhsanudin Murshal Firdany Narado, Jefli Randy Nazrul Effendy Novrian, Willi Nuri, Nuri Hidayati Nurlisis, Nurlisis Prihanto, Surya Putra, Yusran Panca Putri, Rahmayuni Rahmah, Septia Pristi Rahmat Fauzi Rahmat Fauzi Rahmedani Putri, Shindi Ramadhani, Sucy Reni Zulfitri Riswanto Subandi, M Andrea Ritonga, Zabal Rahman Rizka, Yulia Rizki, Sestri Novia Sarah Astiti S.Kom., M.MT Saut Pintubipar Saragih Sinaga, Doni Yoswardi Sinaga Sintar Nababan Sri Rezeki Stephanie Dwi Guna Susanto, Yudi wardiansyah putra Wijaya, Ermy Yulia Yulia Yulia Yulia Yunisman Roni