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Pada project ini, akan dilakukan identifikasi nilai mata uang rupiah dengan menggabungkan metode ekstrasi ciri Local Binary Pattern dan metode klasifikasi Naïve Bayes. Serta untuk pengukuran akurasi identifikasi dilakukan dengan metode evaluasi K-Fold Cross Validation. Dataset yang digunakan berupa citra dengan rincian terdapat 120 citra yang terdiri dari 15 citra uang kertas Rp1.000, 15 citra uang kertas Rp2.000, 15 citra uang kertas Rp5.000, 15 citra uang kertas Rp10.000, 15 citra uang kertas Rp20.000, 15 citra uang kertas Rp50.000, 15 citra uang kertas Rp75.000, dan 15 citra uang kertas Rp100.000

Python 100.00%
citra-digital computer-vision data-science grayscale k-fold-cross-validation local-binary-pattern machine-learning naive-bayes python rupiah uang

rupiah-currency-image-recognition-system's Introduction

Hi there, I'm Weni.

  • 👀 I am a Software Engineer with experience in developing various projects ranging from responsive websites, microservices REST API, desktop and mobile applications, database systems, AI products and more. As someone who loves to learn, what makes me feel passionate to be a software engineer is because this field allows me to keep learning something new such as new programming languages, new frameworks, new libraries, new tools, and more.
  • 💞️ I’m looking to collaborate on project involing software development.

Connect with me:

arnabdey0503 | LinkedIn arnabdey0503 | Instagram

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