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All Journal Social, Humanities, and Educational Studies (SHEs): Conference Series CITIZEN: Jurnal Ilmiah Mulitidisiplin Indonesia
Fahrezi, Wildan Deni
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Religion Humanities Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences

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Deep Learning Based Detection Of Laying Hen Health Status From Excreta Images Using MobileNetV2: Deteksi Status Kesehatan Ayam Petelur Berbasis Deep Learning Dari Citra Ekskreta Menggunakan MobileNetV2 Ni'am, Muhammad Nidhomun; Widiastuti, Sri; Fahrezi, Wildan Deni; Al-Huda, Thoriqul Irfah; Muqofi, Abdul Karim; Mustofa, Rizal Aji; Muafi, Arib Zainul
Citizen : Jurnal Ilmiah Multidisiplin Indonesia Vol. 6 No. 2 (2026): CITIZEN: Jurnal Ilmiah Multidisiplin Indonesia (On Progress)
Publisher : DAS Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53866/jimi.v6i2.1285

Abstract

Early and accurate disease detection is a critical challenge in modern poultry farming. This study aimed to develop and evaluate a deep learning-based classification system using MobileNetV2 Convolutional Neural Network (CNN) architecture for automated detection of poultry diseases from excreta images only, and to validate model predictions against laboratory microbiological analyses. A total dataset of 8,087 labeled excreta images was compiled across four health categories: Healthy, Salmonella, Coccidiosis, and Newcastle Disease, and subsequently split into training (6,471) and validation (1,616) subsets at an 80:20 ratio. The MobileNetV2 model was trained over eight epochs with data augmentation strategies and evaluated using precision, recall, F1-score, accuracy, and confusion matrix analysis. The model achieved an overall accuracy of 91%, with the highest per-class F1-score for Coccidiosis (0.97) and the lowest for Newcastle Disease (0.75). The CNN MobileNetV2 architecture demonstrates strong potential for real-time, non-invasive poultry disease monitoring.
The Need for Augmented Reality Batik Media to Increase Cultural Love for Learning, Drawing, Design, and Craft Production in Vocational High Schools Fahrezi, Wildan Deni; Sariyatun, Sariyatun; Sudiyanto, Sudiyanto
Social, Humanities, and Educational Studies (SHES): Conference Series Vol 8, No 1 (2025): Social, Humanities, and Educational Studies (SHEs): Conference Series
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/shes.v8i1.99114

Abstract

Cinta budaya di sekolah sangat penting, karena selain melestarikan warisan budaya, juga memperkuat identitas, meningkatkan toleransi, dan membangun karakter siswa di tengah masyarakat multikultural. Salah satu cara efektif untuk menumbuhkan rasa cinta budaya adalah melalui inovasi pembelajaran yang menarik dan interaktif. Penelitian ini bertujuan untuk mengidentifikasi kebutuhan Media Batik Augmented Reality sebagai solusi untuk meningkatkan cinta budaya di kalangan siswa SMK dalam pembelajaran Gambar Desain dan Produksi Kriya. Penelitian ini menggunakan pendekatan deskriptif kualitatif untuk mengidentifikasi kebutuhan media batik augmented reality dalam meningkatkan cinta budaya pada pembelajaran gambar desain dan produksi kriya di sekolah menengah kejuruan. Hasil data mengenai ketertarikan siswa terhadap batik menunjukkan bahwa 65% siswa merasa sangat tertarik jika materi batik disampaikan melalui AR, mengindikasikan bahwa teknologi ini berpotensi menarik perhatian siswa dengan cara yang lebih interaktif dan visual. Hasil penelitian yang dilakukan menunjukkan bahwa terdapat  peluang besar dalam pengembangan media pembelajaran batik augmented reality di era digital dalam proses pembelajaran khususnya pada mata pelajaran gambar desain dan produksi kriya di  SMK.
Co-Authors Al-Huda, Thoriqul Irfah Muafi, Arib Zainul Muqofi, Abdul Karim Mustofa, Rizal Aji Ni'am, Muhammad Nidhomun Sariyatun Sariyatun Sri Widiastuti, Sri Sudiyanto Sudiyanto