<![CDATA[Large-scale broiler chicken farming industries often operate with thin profit margins. Manual recording frequently leads to inaccurate data that is unavailable in real-time. This study aims to design a multi-platform Management Information System (MIS) integrated with computer vision technology to enhance operational efficiency, improve production data accuracy, and create a user-friendly system. The system development applies the Waterfall method, utilizing Flutter for desktop and mobile apps, Golang for the backend, and PostgreSQL for the database.Integrating a pre-trained computer vision model via poultry house CCTV automates the estimation of chicken population and mortality. Research results demonstrate the successful integration of four modules: Production Monitoring, Supply Chain Management, Finance and Accounting, and Sales and Distribution. Simulation testing proves potential for improved efficiency and accuracy, supported by usability evaluations indicating good user acceptance. However, this study remains limited to simulated environments, where detection accuracy relies heavily on lighting conditions and camera quality. Industri peternakan ayam broiler berkapasitas produksi besar sering beroperasi dengan margin keuntungan tipis. Pencatatan manual kerap memicu data yang tidak akurat dan tidak tersedia secara real-time. Penelitian ini bertujuan merancang Sistem Informasi Manajemen (SIM) multi-platform terintegrasi teknologi computer vision untuk meningkatkan efisiensi operasional, akurasi data produksi, serta menghasilkan sistem yang user-friendly. Pengembangan sistem menerapkan metode Waterfall, menggunakan Flutter untuk aplikasi desktop dan mobile, Golang pada backend, serta PostgreSQL sebagai basis data. Sistem ini mengintegrasikan pre-trained model computer vision melalui CCTV kandang untuk mengotomatisasi estimasi populasi dan mortalitas ayam. Hasil penelitian menunjukkan keberhasilan integrasi empat modul: Production Monitoring, Supply Chain Management, Finance and Accounting, serta Sales and Distribution. Pengujian simulasi membuktikan potensi peningkatan efisiensi dan akurasi, didukung oleh evaluasi usability dengan tingkat penerimaan pengguna yang baik. Namun, penelitian masih dibatasi pada lingkungan simulasi, di mana akurasi deteksi sangat bergantung pada kondisi pencahayaan dan kualitas kamera.]]>
