Pengembangan Aplikasi Pemantauan Waktu Nyata Aktivitas Juru Las dan Kualitas Hasil Las Berbasis Data Hasil Sensor Gerakan Tangan Dan QR Code

Aji, Adi Sasmito (2025) Pengembangan Aplikasi Pemantauan Waktu Nyata Aktivitas Juru Las dan Kualitas Hasil Las Berbasis Data Hasil Sensor Gerakan Tangan Dan QR Code. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Penelitian ini bertujuan untuk mengembangkan aplikasi pemantauan waktu nyata aktivitas juru las dan kualitas hasil las berbasis data sensor gerakan tangan dan kode QR. Pada penelitian sebelumnya telah dikembangkan penggunaan kombinasi sensor gerak Inertial Measurement Unit (IMU) yang dilekatkan pada pergelangan tangan, Internet of Things (IoT), dan teknologi Artificial Intelligence (AI) untuk mengenali aktivitas dan kinerja juru las sehingga dapat diklasifikasikan. Namun, sistem tersebut belum mampu mengidentifikasi bagian konstruksi dan sambungan (joint design) yang sedang dilakukan pengelasan. Selain itu, dikembangkan juga penggunaan teknologi QR-Code untuk membantu juru las mengakses informasi tugas, Welding Procedure Specification (WPS), serta lokasi pengelasan dalam proses pembangunan kapal. Pada pada penelitian ini dilakukan integrasi teknologi sensor gerakan tangan dan kode QR sehingga aktivitas juru las dan kualitas hasil las dapat dipantau secara real time serta lokasi pengelasan dan joint design pada konstruksi dapat teridentifikasi secara otomatis. Sistem dikembangkan dengan memanfaatkan kode QR dan ponsel cerdas berbasis Android. Data gerakan tangan yang direkam sensor IMU langsung ditransfer ke penyimpanan ponsel melalui koneksi Bluetooth, kemudian diunggah ke penyimpanan awan melalui koneksi internet. Data rekaman dianalisis menggunakan metode deep learning dan dibandingkan dengan tampilan visual hasil las yang dilaporkan oleh juru las setelah proses pengelasan selesai. Posisi pengelasan diidentifikasi secara otomatis melalui kode QR oleh sistem Android. Uji coba pada skala laboratorium menunjukkan bahwa sistem dapat membantu juru las untuk mengakses informasi tugas, WPS, dan lokasi pengelasan secara efektif, serta membantu welding engineer dalam memantau aktivitas juru las, kualitas hasil las, dan lokasi pengelasan secara real time.
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This research aims to develop a real-time monitoring application for welder activities and weld quality based on hand motion sensor data and QR codes. Previous studies have developed the use of a combination of Inertial Measurement Unit (IMU) motion sensors attached to the wrist, the Internet of Things (IoT), and Artificial Intelligence (AI) technology to recognize welder activities and performance for classification purposes. However, the system was not yet capable of identifying the construction parts and joint designs where welding was performed. Additionally, the use of QR-Code technology was developed to assist welders in accessing task information, Welding Procedure Specification (WPS), and welding locations during shipbuilding. In this research, the integration of hand motion sensor technology and QR codes is conducted so that welder activities and weld quality can be monitored in real time, while welding locations and joint designs on the construction can be automatically identified. The system is developed by utilizing QR codes and Android-based smartphones. Hand motion data recorded by IMU sensors are transferred directly to smartphone storage via Bluetooth connection, then uploaded to cloud storage through an internet connection. The recorded data is analyzed using deep learning methods and compared with the visual appearance of welds reported by the welders after the welding process is completed. The welding position is automatically identified through QR codes by the Android system. Laboratory-scale testing shows that this system can effectively assist welders in accessing task information, WPS, and welding locations, as well as help welding engineers monitor welder activities, weld quality, and welding locations in real time.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Pemantauan Aktivitas Juru Las, Sensor Gerak Pergelangan Tangan, QR Code, Welder Activity Monitoring, Wrist Motion Sensor, QR Code.
Subjects:	V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering
Divisions:	Faculty of Marine Technology (MARTECH) > Naval Architecture and Shipbuilding Engineering > 36101-(S2) Master Thesis
Depositing User:	Adi Sasmito Aji
Date Deposited:	14 Aug 2025 04:35
Last Modified:	14 Aug 2025 04:35
URI:	http://repository.its.ac.id/id/eprint/128089

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