Classification of Rupiah to Help Blind with The Convolutional Neural
Network Method

Classification of Rupiah to Help Blind with The Convolutional Neural
Network Method

Blind, Currency, Deep Learning, CNN, Epoch

Currency is an item humans require as a medium of exchange in transactions, including for those with vision impairments. It
can be challenging for certain blind people to identify currencies. This research aimed to help blind people identify nominal
currency when in the transaction. Deep Learning with the CNN algorithm and preprocessing with a sequential model were the
methods used in this research. This algorithm is modeled as neurons in the human brain that communicate and learn patterns.
Data collecting, preprocessing, testing, and evaluation are the stages in this research. 681 datasets are used, consisting of IDR
50.000, IDR 75.000, and IDR 100.000. Model testing was carried out with different iterations of 5, 10, 15, and 20 epochs.
Different epoch values will affect the time it takes the model to learn, but the longer of learning process will result more
accurate models. The highest result obtained from all epoch tests is 100%. The class prediction results for the 69 test data
show that they can be predicted based on the actual class, indicating that the model is adequate. The results of this classification
might be used to construct a smartphone app that would assist visually challenged people in recognizing the nominals

Octavian Ery Pamungkas1
, Puspa Rahmawati2
, Dhany Maulana Supriadi3
, Natasya Nur Khalika4
, Thofan
Maliyano5
, Dicky Revan Pangestu6
, Eka Setia Nugraha7
, Mas Aly Afandi8
, Nurcahyani Wulandari9
, Petrus
Kerowe Goran10, Agung Wicaksono11

Octavian Ery Pamungkas1
, Puspa Rahmawati2
, Dhany Maulana Supriadi3
, Natasya Nur Khalika4
, Thofan
Maliyano5
, Dicky Revan Pangestu6
, Eka Setia Nugraha7
, Mas Aly Afandi8
, Nurcahyani Wulandari9
, Petrus
Kerowe Goran10, Agung Wicaksono11

29-04-2022

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