Prototipe Detektor Mata Uang Kertas Untuk Modul Vending Machine Automatic Cash Money Menggunakan Rapsberry Pi

Sigit Anggoro, Tacbir Hendro

Abstract

Vending Machines are strategic trading machines when it comes to social and physical distancing policies during the current Covid 19 pandemic. The ability to trade independently in trading without a physical meeting is one of its advantages. On the other hand, the Vending Machine payment system has developed with many variations ranging from payment models using coins, banknotes, payment gateway systems capable of serving debit and credit payments and the ability to make payments via fintech. This study focuses on the banknote detection module using the Oriented FAST and Rotated BRIEF (ORB) algorithm. In order to become a prototype that is ready to be developed in the future, the banknote detection module needs to be made in a concise and independent form. The use of the Rapsberry Pi and the ability to work on complex algorithms is one of the goals that will be achieved from this research. This research is expected to be able to apply the ORB algorithm for the classification of Rupiah banknotes and at the same time be able to further develop it to sort (sort) for banknotes that meet the requirements (accept) and reject those that do not meet the requirements (reject).

Keywords

Vending Machine; Klasifikasi ; mata uang kertas ;ORB; Rapsberry Pi

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References

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