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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Informatika dan Teknik Elektro Terapan Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) ELINVO (Electronics, Informatics, and Vocational Education) Creative Information Technology Journal CogITo Smart Journal Voice Of Informatics Majalah Ilmiah UNIKOM Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat CSRID (Computer Science Research and Its Development Journal) METIK JURNAL SENSITEK E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi JATI (Jurnal Mahasiswa Teknik Informatika) IT (INFORMATIC TECHNIQUE) JOURNAL Informatics and Digital Expert (INDEX) INFOSYS (INFORMATION SYSTEM) JOURNAL JURNAL REKAYASA INFORMASI SWADHARMA (JRIS) JURNAL ELEKTRO DAN INFORMATIKA SWADHARMA (JEIS) PUBLIDIMAS CSRID Jurnal Pengabdian Masyarakat (JURDIMAS) Jurnal Sistem Informasi dan Teknologi Informasi
Teuku Mufizar
Universitas Perjuangan Tasikmalaya
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

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Journal : iaes international journal of artificial intelligence ij-ai

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Classification of Tasikmalaya batik motifs using convolutional neural networks Mufizar, Teuku; Sudiarjo, Aso; Dewi Sri Mulyani, Evi; Ahmad Wakih, Agus; Akbar Kasyfurrahman, Muhammad; Adilal Mahbub, Luthfi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i4.pp3287-3299

Abstract

This paper presents a study on the classification of traditional Tasikmalaya batik motifs using convolutional neural networks (CNN). The experiments revealed that the high complexity of batik motifs significantly impacted model performance, as the handling of each class influenced the overall results. Initial experiments with the original dataset demonstrated suboptimal performance, characterized by accuracy and validation curves indicating overfitting, with only 75% accuracy achieved at a learning rate of 0.001, a batch size of 32, and 50 epochs. To enhance performance, we implemented data segmentation, data augmentation, optimized the choice of the best optimizer, utilized an optimal architecture, and conducted hyperparameter tuning. The best-performing model was trained on data subjected to specific preprocessing for each class, using the Adam optimizer with hyperparameter tuning set to a learning rate of 0.001, a batch size of 32, and 50 epochs. In the hyperparameter tuning experiment with the visual geometry group network (VGGNet) architecture, it was shown that there is an improvement in the prediction of the kumeli class, achieving an accuracy of 100%.
Classification of Cihateup duck egg fertility using convolutional neural network EfficientNet-B3 Dewi Sri Mulyani, Evi; Mufizar, Teuku; Rohpandi, Dani; Djuliani, Ayu; Rahmatulloh, Egi; Satia Aulia Rahmat, Rinaldi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i1.pp798-809

Abstract

Accurate detection of egg fertility is crucial to improve hatching success in duck farming. Conventional candling methods rely heavily on human expertise, making them subjective and error-prone. This study proposes an automated classification system for Cihateup duck egg fertility using candling images and a convolutional neural network (CNN) based on the EfficientNet-B3 architecture. Image enhancement techniques, including contrast limited adaptive histogram equalization (CLAHE), unsharp masking, and adaptive thresholding, were applied to improve image quality and feature visibility. The dataset consisted of fertile and infertile egg images captured at two incubation stages: the first 24 hours and the 8th–15th days. Data were split into training, validation, and testing sets with a ratio of 70:15:15. Experimental results show that image enhancement significantly improves classification performance. Without enhancement, the model achieved an accuracy of 49% with an area under curve (AUC) of 0.4226, indicating poor discrimination capability. With image enhancement, the proposed method achieved accuracies of 77% for the first 24 hours dataset and 80% for the 8th–15th days dataset, with AUC values of 0.9962 and 0.9317, respectively. These results demonstrate that EfficientNet-B3 combined with image enhancement provides an effective and computationally efficient solution for automated fertility detection of Cihateup duck eggs.
Co-Authors Abdulrohman, Rijal Adilal Mahbub, Luthfi Agus Supriatman Agustin, Anggi Permana Ahmad Wakih, Agus Akbar Kasyfurrahman, Muhammad Alma Husna Hanifah Amelia Dewi Sani Septiani Andriani, Aan Aprianis, Epa Ardiani, Annisa Arianti Salama Arifatun Nasuha Awit Marwati Sakinah Aysicom Paraguay, Muhammad Ayu Rahmawati Cepi Rahmat Hidayat Cepi Rahmat Hidayat Cepy Rahmat Hidayat Cepy Rahmat Hidayat Chaeruddin, Rofi Dani Rohpandi Dede Sahrul Anwar Dede Syahrul Anwar Dede Syahrul Anwar Dede Syahrul Anwar Dede Syahrul Anwar, Dede Syahrul Dikdik Muhammad Siddiq Dinda Sofi Farhani Djuliani, Ayu Egi Badar Sambani, Egi Badar Estie Alfiyani Evi Dewi Sri Mulyani Fahroni, Rizal Farhani, Dinda Sofi Farid Hamzah Firna Pebrianti Fortuna Gilang Muhammad Nur Alip Gustaman, R Joni Gustiar Firmansyah, Nizar Hartiwan, Intan Herdi Muhammad Syaban Hidayatuloh, Ade Taopik Hikmatyar, Missi Indah Septianingrum Indradewa, Rhian Intan Hartiwan Kasyfurrahman, M. Akbar Khairul Anwar Kurdiman Kurdiman Kurdiman Ari Kurdiman, Kurdiman Lestari, Rima Listiani Lina Listiani linggar nursinggah Ma'ruf, Jamal Maulana, Akmal Mira Yuliani Muhamad Rizky Fadillah Muhamad Satrio Nugraha N. Nelis Febriani SM Nanang Suciyono, Nanang Nelis Nurjayanti, Nelis Nugraha, Muhammad Rizki nursinggah, linggar Pramana, Hendri Julian Rahadi Deli Saputra Rahmatulloh, Egi Restu Adi Wiyono Rismansyah, Riki Roska Robby Awaludin Rudi Hartono Rustin Kania Dewi Ruuhwan Ruuhwan Ruuhwan Salsabila, Halda Sarmidi Sarmidi Sarmidi Sarmidi Satia Aulia Rahmat, Rinaldi Shafarulloh, M. Hisyam Shinta Siti Sundari Sofiani, Efin Sudiarjo, Aso Susanto Susanto Syaban, Herdi Muhammad Teten Nuraen Tina Kumala Wahyu Kamaludin Wakih, Agus Ahmad Wulansari, Nindi Ayu Yuda Purnama Putra Yusep Rosmansyah Yusuf Sumaryana