Penerapan Computer Vision Menggunakan Model Yolov8 Untuk Monitoring Kepadatan Pengunjung Ruang Rawat Inap Di Rumah Sakit
Abstract
Abstract: Hospitals, as healthcare facilities, have a high level of visitor mobility, particularly in inpatient wards. Therefore, visitor control is necessary to maintain patient comfort, safety, and service quality. Manual visitor monitoring is considered ineffective and prone to errors. Therefore, this study aims to design and implement an artificial intelligence-based visitor monitoring system for hospital inpatient wards using computer vision technology. The developed system utilizes the YOLOv8 model as an object detection algorithm to automatically detect and count visitors through a camera. Visitor information is displayed through a desktop-based monitoring interface and is equipped with warning notifications via the Telegram application and an automatic alarm if the number of visitors exceeds the limit set by hospital policy. Test results show that the system is capable of performing well in detecting and counting visitors in real time, as well as sending information and warnings responsively. Thus, this system is considered effective as a technology-based hospital management support solution in controlling inpatient ward density and making decisions more quickly and accurately.
Keywords: hospital; inpatient ward; computer vision; yolov8; visitor monitoring
Abstrak: Rumah sakit sebagai fasilitas pelayanan kesehatan memiliki tingkat mobilitas pengunjung yang tinggi, khususnya pada ruang rawat inap, sehingga diperlukan pengendalian jumlah pengunjung untuk menjaga kenyamanan, keselamatan pasien, dan kualitas pelayanan. Pemantauan jumlah pengunjung secara manual dinilai kurang efektif dan rentan terhadap kesalahan. Oleh karena itu, penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem pemantauan jumlah pengunjung ruang rawat inap rumah sakit berbasis kecerdasan buatan menggunakan teknologi computer vision. Sistem yang dikembangkan memanfaatkan model YOLOv8 sebagai algoritma object detection untuk mendeteksi dan menghitung jumlah pengunjung secara otomatis melalui kamera. Informasi jumlah pengunjung ditampilkan melalui antarmuka pemantauan berbasis desktop dan dilengkapi dengan notifikasi peringatan melalui aplikasi Telegram serta alarm otomatis apabila jumlah pengunjung melebihi batas yang ditetapkan sesuai kebijakan rumah sakit. Hasil pengujian menunjukkan bahwa sistem mampu bekerja dengan baik dalam mendeteksi dan menghitung jumlah pengunjung secara real-time, serta mengirimkan informasi dan peringatan secara responsif. Dengan demikian, sistem ini dinilai efektif sebagai solusi pendukung manajemen rumah sakit berbasis teknologi dalam pengendalian kepadatan ruang rawat inap dan pengambilan keputusan yang lebih cepat dan akurat.
Kata kunci: rumah sakit; ruang rawat inap; computer vision; yolov8; monitoring pengunjung
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