Gracia, Cathleen and Adhitthana, Daniel (2026) Riset Pengembangan Aplikasi Monitoring Kantin Petikemas Teknik Sistem dan Industri ITS. Project Report. [s.n.]. (Unpublished)
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Abstract
Kantin Petikemas Teknik Sistem dan Industri ITS merupakan fasilitas yang digunakan oleh mahasiswa dan staf untuk beraktivitas sehari-hari. Pengelolaan informasi mengenai jumlah pengunjung serta area yang paling sering dikunjungi masih belum terdokumentasi secara sistematis. Oleh karena itu, diperlukan sebuah sistem yang mampu melakukan pemantauan dan penyajian data kunjungan secara otomatis. Pada kerja praktik ini dilakukan riset pengembangan aplikasi monitoring kantin berbasis web yang memanfaatkan kamera CCTV dan teknologi visi komputer. Sistem menggunakan model YOLO yang telah dilatih untuk melakukan segmentasi serta klasifikasi pengunjung berdasarkan gender. Pengunjung akan dihitung sebagai pengunjung ketika melewati area tertentu yang telah ditentukan, sementara area lain dapat diberi anotasi berbentuk bounding box untuk menganalisis popular location di dalam kantin. Aplikasi dikembangkan menggunakan backend Go dan Python, frontend Svelte, serta basis data MongoDB dan PostgreSQL. Sistem menyediakan dashboard untuk menampilkan statistik jumlah pengunjung berdasarkan waktu, tampilan CCTV secara langsung, serta fitur anotasi area pemantauan. Dengan adanya sistem ini, informasi mengenai aktivitas pengunjung kantin dapat diperoleh secara lebih terstruktur dan mudah dianalisis.
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The Petikemas Canteen of the ITS Industrial and Systems Engineering Department is a facility used by students and staff for their daily activities. Information management regarding the number of visitors and the most frequently visited areas has not been systematically documented. Therefore, a system capable of automatically monitoring and presenting visit data is needed. In this internship, research was conducted on the development of a web-based canteen monitoring application that utilizes CCTV cameras and computer vision technology. The system uses a trained YOLO model to segment and classify visitors based on gender. Visitors will be counted as visitors when they pass through certain predetermined areas, while other areas can be annotated in the form of bounding boxes to analyze popular locations within the canteen. The application was developed using a Go and Python backend, a Svelte frontend, and MongoDB and PostgreSQL databases. The system provides a dashboard to display visitor statistics based on time, live CCTV views, and annotation features for monitoring areas. With this system, information about canteen visitor activity can be obtained in a more structured and easily analyzed manner.
| Item Type: | Monograph (Project Report) |
|---|---|
| Uncontrolled Keywords: | Computer Vision, YOLO, Monitoring Pengunjung, Dashboard Web, CCTV |
| Subjects: | T Technology > T Technology (General) T Technology > T Technology (General) > T57.6 Operations research--Mathematics. Goal programming T Technology > T Technology (General) > T59.7 Human-machine systems. |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Informatics Engineering > 55201-(S1) Undergraduate Thesis |
| Depositing User: | Cathleen Gracia |
| Date Deposited: | 07 Jul 2026 06:18 |
| Last Modified: | 07 Jul 2026 06:18 |
| URI: | http://repository.its.ac.id/id/eprint/134214 |
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