Penerapan Algoritme Regular Expression Dalam Aplikasi Pendeteksi Nominal Uang Kertas
Abstract
The visual limitations of persons with visual disabilities, especially those who are in a state of total blindness, make them recognize nominal money through touch. It's just that the usual tactile techniques used are not effective enough. This paper presents an application model for detecting Rupiah nominal currency, using the Regular Expression algorithm. The cellphone camera is enabled to take pictures of Rupiah banknotes, then convert them into a text format using Optical Character Recognition (OCR) technology. The Regular Expression algorithm is enabled to find nominal patterns in the text generated by OCR. The output of the system is in the form of a certain nominal vibration based on the detected nominal value of the currency. The Talkback Accessibility feature on Android will also generate a Nominal Voice accompanying the on-screen message. Test results on 21 samples of Rupiah banknotes in various denominations involving 10 blind respondents showed that the system model developed had an accuracy rate of up to 100% in testing 210 data samples.
Keywords: Detection of banknotes; Optical Character Recognition; Regular Expression algorithm; Visual Disabilities
Abstrak
Keterbatasan penglihatan penyandang disabilitas netra, terutama yang berada pada kondisi mengalami kebutaan total, membuat mereka mengenali nominal uang melalui perabaan. Hanya saja teknik perabaan yang biasa digunakan belum cukup efektif. Makalah ini menyajikan model aplikasi pendeteksi nominal mata uang kertas Rupiah, dengan menggunakan algoritme Regular Expression. Kamera handphone difungsikan untuk mengambil gambar uang kertas Rupiah, lalu mengubahnya menjadi format teks menggunakan teknologi Optical Character Recognition (OCR). Algoritme Regular Expression difungsikan untuk mencari pola nominal pada teks yang dihasilkan oleh OCR. Output sistem berupa Getar Nominal tertentu berdasarkan nilai nomonal mata uang yang dideteksi. Fitur Aksesibilitas Talkback pada Android juga akan menghasilkan Suara Nominal yang menyertai pesan di layar. Hasil uji terhadap 21 sampel uang kertas Rupiah dalam berbagai nilai pecahan, dengan melibatkan 10 responden penyandang tunanetra menunjukkan model sistem yang dikembangkan memiliki tingkat akurasi mencapai 100% pada pengujian 210 sampel data.
Kata Kunci: Deteksi uang kertas; Optical Character Recognition; algoritme Regular Expression; Disabilitas Netra
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