Indonesian Banknote Value Recognizer is a computer vision application that was built in Python and implemented to GUI using Python Tkinter. This model is intended to recognize Indonesian banknote value in various environments and conditions, such as in a crumpled and wrinkled banknotes. This project performs data preprocessing using OpenCV, clustering using K-Means Clustering, and predicting the result using SVM (Support Vector Machine). The application is implemented to GUI using Python Tkinter. This project is created as a final project in the Computer Vision course. The explanation of the project can be accessed from this link.

• Nadya Tyandra - Machine Learning Engineer
• Randy Antonio - Machine Learning Engineer
• Edwin Ario Abdiwijaya - Machine Learning Engineer