Skripsi

RANCANG BANGUN SISTEM KLASIFIKASI SAMPAH LOGAM MEDIS BERBASIS ESP32-CAM DENGAN INTEGRASI SENSOR LOGAM INDUKTIF

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Medical metal waste such as syringes and scalpels are Hazardous and Toxic Waste (B3) which has the potential to cause injury, infection, and environmental pollution if not managed properly. This study aims to design and build a medical metal waste classification system based on ESP32-CAM with integrated inductive metal sensors to assist the automatic waste sorting process. The research method used is the design method which includes hardware design, software, implementation, and system testing. The system consists of ESP32 as the main controller, ESP32-CAM as an image capture device, an infrared sensor as an object detector, an inductive metal sensor as a metal detector, and a Python server that runs the FOMO-based artificial intelligence model from Edge Impulse. The test results show that the inductive metal sensor has a 100% success rate in detecting metal objects, the artificial intelligence model achieves 90% accuracy, and the integrated system produces a sorting accuracy of 100% on 10 test data. These results indicate that the system is capable of classifying and sorting medical metal waste automatically, safely, and effectively.

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Availability

Detail Information

Series Title

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Call Number

T2013262026

Publisher

Palembang : Prodi Diploma III Teknik Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2026

Collation

xiv, 66 hlm.; ilus.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

621.381 07

Content Type

Text

Media Type

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Carrier Type

-

Edition

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Subject(s)

Prodi Diploma III Teknik Komputer
Mikrokontroler ESP32 dan Sistem Sensor

Specific Detail Info

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Statement of Responsibility

MI

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