Sistem Pendeteksi Baju Operasi Berbasis Image Processing

Hidayattulah, Rizal (2025) Sistem Pendeteksi Baju Operasi Berbasis Image Processing. Sarjana (S1) thesis, Universitas Islam 45.

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Abstract

Surgical gowns are specialized clothing that must be worn in sterile hospital areas to maintain cleanliness and prevent contamination. To enhance monitoring and safety, this study developed an automatic surgical gown detection system using a camera and Raspberry Pi as the main processing unit. The system operates by detecting the presence of an object in front of a door; if a surgical gown is detected, the door automatically opens via solenoid control, while if not, a buzzer is activated as a warning. The detection model used is YOLOv8, which was trained to recognize the characteristics of surgical gowns based on color and shape. Test results show that the system achieved a detection accuracy of 100%, with no false detections of regular clothing. The system can optimally detect objects within a distance range of 1 to 2 meters, and it can recognize individuals with a height range of 150 cm to 200 cm. Furthermore, the system responds in under 1 second and operates stably without interruption. Based on these results, the system is considered effective and suitable for use in hospital environments to support sterilization procedures and operational safety. Keywords: Surgical gown, Raspberry Pi, YOLOv8, automatic detection, camera, hospital safety system.

Item Type: Thesis (TA, Skripsi, Tesis, Disertasi) (Sarjana (S1))
Contributors/Dosen Pembimbing,NIDN Dosen bisa diakses di LINK https://bit.ly/NIDNdosenunismabekasi:
ContributionContributors / Dosen PembimbingNIDN
UNSPECIFIEDFirasanti, Anisa0412108901
UNSPECIFIEDSikki, Muhammad Ilyas0409017104
Keywords / Kata Kunci: Kata kunci: Baju operasi, Raspberry Pi, YOLOv8, deteksi otomatis, kamera, sistem keamanan rumah sakit.
Subjects: Elektronik
Faculty: Fakultas Teknik > Teknik Elektro S1
Depositing User: Mr. Rizal Hidayattulah
Date Deposited: 19 Sep 2025 09:34
Last Modified: 19 Sep 2025 09:34
URI: http://repository.unismabekasi.ac.id/id/eprint/8637

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