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All Journal Brilliance: Research of Artificial Intelligence Jurnal Solusi Masyarakat (JSM)
Fadlisyah Fadlisyah
Universitas Malikussaleh, Indonesia
Agriculture, Biological Sciences & Forestry Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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Video-Based Disease Detection in Vannamei Shrimp Using YOLOv8 Architecture Fathurrahman Siregar; Fadlisyah Fadlisyah; Hafizh Al Kautsar Aidilof
Brilliance: Research of Artificial Intelligence Vol. 6 No. 2 (2026): Brilliance: Research of Artificial Intelligence, Article Research May 2026
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v6i2.8613

Abstract

Vannamei shrimp (Litopenaeus vannamei) is a high-value aquaculture commodity that significantly contributes to the fisheries sector. However, shrimp farming faces a high risk of disease outbreak to mass mortality and substantial economic losses. Conventional health detection methods rely on manual observation, which is subjective, inefficient, and requires expert knowledge. Therefore, this study proposes an automated shrimp health detection system based on video imagery using Convolutional Neural Networks (CNN) implemented through the YOLOv8 algorithm.The dataset consists of 2,000 images extracted from video frames of vannamei shrimp and categorized into healthy and diseased classes. The research methodology includes data preprocessing, augmentation, model training, and evaluation using performance metrics such as precision, recall, and mean Average Precision (mAP). The trained model is deployed in a web-based system using FastAPI and OpenCV to enable real-time detection. Experimental results show that the proposed CNN-based model achieves an mAP@0.5 of approximately 0.92 (92%), with precision and recall values of approximately 0.85 and 0.90, respectively. These results indicate strong detection performance under real-world conditions. The system is capable of automatically identifying shrimp health conditions and provides higher efficiency compared to manual inspection. This study demonstrates that deep learning-based computer vision has strong potential for early disease detection and can support sustainable aquaculture management
Penguatan Kompetensi Pelatih Silat Perisai Diri melalui Pendekatan Reflektif dalam Ujian Kenaikan Tingkat Asrianda Asrianda; Padmono Wibowo; Nasrul ZA; Fadlisyah Fadlisyah; Kurniawati Kurniawati; Nirzalin Nirzalin
Jurnal Solusi Masyarakat (JSM) Vol. 4 No. 2 (2026)
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jsm.v4i2.29599

Abstract

This Community Service Program (CSP) aims to strengthen pre-service teachers’ competence in implementing local wisdom-based learning at Madrasah. The program responds to the gap between pre-service teachers’ knowledge of Acehnese local wisdom and their ability to transform cultural values into contextual and meaningful learning experiences. A participatory and experiential learning approach was employed through five stages: needs assessment, competency strengthening, instructional design, microteaching, and supervised classroom practice, followed by reflection and mentoring. Program activities focused on strengthening local wisdom literacy, pedagogical content knowledge, instructional design, teaching practice, and reflective competence. Participants were trained to identify educational values embedded in local wisdom, including Hadih Maja, meuseuraya, respect for parents and teachers, and traditions of deliberation, and integrate these values into learning objectives, materials, activities, methods, and assessment. Program effectiveness was evaluated through pre-test and post-test comparisons, teaching-performance observation, assessment of instructional products, and participant reflection. The expected outcomes include improved pedagogical competence, practical instructional skills, and the production of contextual learning materials. The program also promotes a sustainable model through a local wisdom-based learning resource bank and community of practice. The program seeks to develop culturally responsive pre-service teachers capable of transforming local wisdom into authentic and meaningful learning experiences.
Co-Authors Asrianda Asrianda Fathurrahman Siregar Hafizh Al Kautsar Aidilof Kurniawati Kurniawati Nasrul ZA Nirzalin Nirzalin Padmono Wibowo