Adelia Clarissa, - and Anugrah Adiwilaga, - and Deden Pradeka, - (2025) PENGEMBANGAN SISTEM CELENGAN PINTAR BERBASIS IOT DENGAN TEKNOLOGI COMPUTER VISION UNTUK DETEKSI NOMINAL UANG. S1 thesis, Universitas Pendidikan Indonesia.
Abstract
Menabung merupakan kebiasaan yang penting untuk membangun literasi keuangan sejak dini, namun metode tradisional seperti celengan masih memiliki keterbatasan, terutama dalam hal keamanan dan transparansi. Penelitian ini bertujuan untuk melakukan perancangan serta menguji kinerja celengan pintar berbasis Internet of Things (IoT) dan computer vision sebagai solusi inovatif untuk menjembatani kelemahan menabung dengan metode tradisional maupun digital. Metode penelitian yang digunakan adalah Design and Development (D&D) dengan Artificial Intelligence Life Cycle (AILC) untuk pengembangan model YOLOv8 dalam pendeteksian nominal uang, pendekatan model prototype untuk perancangan perangkat IoT, serta Software Development Life Cycle (SDLC) untuk perancangan web. Hasil penelitian ini menunjukkan bahwa celengan pintar memanfaatkan teknologi RFID untuk identifikasi pengguna, computer vision untuk mendeteksi nominal uang, notifikasi melalui Telegram, serta website sebagai media monitoring tabungan. Model deteksi nominal uang mampu mengenali uang dengan rata-rata tingkat akurasi 62,2% untuk keseluruhan uang dan pada nominal Rp5.000 mencapai tingkat keberhasilan tertinggi sebesar 95% pada lux 40. Perangkat keras bekerja sesuai fungsionalitasnya, sementara perangkat lunak terbukti berjalan sesuai skenario melalui black box testing. Secara keseluruhan, perancangan dan kinerja sistem celengan pintar berbasis IoT dengan teknologi computer vision dalam mendeteksi nominal uang berhasil dilakukan dan berjalan cukup baik, sehingga perangkat keras berjalan sesuai fungsionalitasnya, serta perangkat lunak mampu berjalan sesuai rancangan. ------- Saving is an essential habit to build financial literacy from an early age, yet traditional methods such as piggy banks still face limitations, particularly in terms of security and transparency. This research aims to design and evaluate the performance of a smart piggy bank based on the Internet of Things (IoT) and computer vision as an innovative solution bridging the weaknesses of both traditional and digital saving methods. The study applies the Design and Development (D&D) approach with the Artificial Intelligence Life Cycle (AILC) for developing a YOLOv8 model in currency denomination detection, the prototype model for IoT device design, and the Software Development Life Cycle (SDLC) for web development. The results show that the smart piggy bank integrates RFID for user identification, computer vision for money detection, Telegram notifications, and a web application for savings monitoring. The detection model achieved an average accuracy of 62.2% across all denominations, with the highest performance of 95% for the Rp5,000 note under 40 lux illumination. The hardware operated according to its intended functionality, while the software was validated through black box testing and performed as designed. Overall, the smart piggy bank system utilizing IoT and computer vision successfully demonstrated reliable functionality in both hardware and software, making it a feasible solution for improving the saving experience.
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| Item Type: | Thesis (S1) |
|---|---|
| Additional Information: | https://scholar.google.com/citations?view_op=list_works&hl=en&user=KDKUh1cAAAAJ ID SINTA Dosen Pembimbing: Anugrah Adiwilaga, S.ST., M.T.: 6745914 Deden Pradeka, S.T., M.Kom.: 6680849 |
| Uncontrolled Keywords: | Celengan, Uang, IoT, Computer Vision, Piggy Bank, Money, IoT |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) |
| Divisions: | UPI Kampus cibiru > S1 Teknik Komputer |
| Depositing User: | Adelia Clarissa |
| Date Deposited: | 19 Sep 2025 08:30 |
| Last Modified: | 19 Sep 2025 08:31 |
| URI: | http://repository.upi.edu/id/eprint/137775 |
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