PROTOTIPE OTOMASI PENYORTIRAN KANULA DALAM SISTEM DAUR ULANG LIMBAH MEDIS

MUHAMMAD KHAIRIL ZAKI, . (2025) PROTOTIPE OTOMASI PENYORTIRAN KANULA DALAM SISTEM DAUR ULANG LIMBAH MEDIS. Sarjana thesis, UNIVERSITAS NEGERI JAKARTA,.

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Abstract

Pengelolaan limbah medis, khususnya jarum suntik, menjadi tantangan di Indonesia karena termasuk limbah Bahan Berbahaya dan Beracun (B3) yang berpotensi menyebarkan penyakit dan merusak lingkungan jika tidak ditangani baik. Pemisahan plastik dan kanula logam sangat penting untuk daur ulang dan nilai ekonomis, namun proses manual saat ini kurang efisien. Penelitian ini mengembangkan prototipe sistem sortir otomatis untuk memisahkan kanula logam dari plastik pada jarum suntik hancur, dilengkapi fitur real-time untuk data berat dan estimasi nilai ekonomis. Prototipe menggunakan ESP32, sensor load cell, aktuator magnetik, solenoid, dan konveyor, dengan data ditampilkan via OLED dan antarmuka web, serta disimpan di Firebase. Pengujian menunjukkan akurasi sensor load cell 95%-100% dan pemilahan rata-rata 93,50% pada 80 gram/siklus. Kegagalan terjadi akibat posisi kanula dan kecepatan konveyor, namun penyesuaian PWM 69 meningkatkan stabilitas. Sistem berhasil otomatis, terhubung ke cloud, dan menampilkan estimasi nilai ekonomis, meski terbatas pada kapasitas kecil dan posisi kanula. Pengembangan selanjutnya dapat melibatkan sensor kamera dan optimasi mekanik. Kata Kunci: Limbah Medis, Sortir Otomatis, Pemisahan Logam, Sensor Load cell ***** The management of medical waste, particularly syringes, poses a significant challenge in Indonesia as it falls under Hazardous and Toxic Materials (B3), with the potential to spread infectious diseases and harm the environment if not handled properly. Separating plastic and metal cannula components is crucial for recycling and economic value, yet the current manual process lacks efficiency. This research develops a prototype of an automatic sorting system to separate metal cannulas from plastic in crushed syringes, featuring real-time weight data and economic value estimation. The prototype integrates an ESP32 microcontroller, load cell sensor, magnetic actuators (ferrite magnet and solenoid), and a conveyor, with data displayed via OLED and a web interface, stored in Firebase. Testing showed the load cell sensor accuracy ranges from 95%-100%, with an average sorting accuracy of 93.50% across 80-gram cycles. Failures occurred due to improper cannula positioning and high conveyor speed, but adjusting PWM to 69 improved stability. The system successfully operates automatically, connects to the cloud, and displays economic value estimates, though limited by small capacity and cannula positioning. Future development could include camera-based sensors and mechanical design optimization. Keywords: Medical Waste, Automatic Sorting, Metal Separation, Load Cell Sensor

Item Type: Thesis (Sarjana)
Additional Information: 1). Syufrijal, S.T., M.T. ; 2). Nur Hanifah Yuninda, S.T., M.T.
Subjects: Teknologi dan Ilmu Terapan > Teknologi (umum)
Teknologi dan Ilmu Terapan > Teknik Mesin, Mekanika Teknik
Teknologi dan Ilmu Terapan > Teknik Elektronika
Teknologi dan Ilmu Terapan > Kerajinan Tangan
Divisions: FT > D IV Teknologi Rekayasa Otomasi
Depositing User: Muhammad Khairil Zaki .
Date Deposited: 11 Aug 2025 05:42
Last Modified: 11 Aug 2025 05:42
URI: http://repository.unj.ac.id/id/eprint/59524

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