Implementasi Speech Recognition Pada Aplikasi E-Prescribing Menggunakan Algoritme Convolutional Neural Network

 (*)Nur Azis Mail (Universitas Krisnadwipayana, Jakarta, Indonesia)
 Herwanto Herwanto (Universitas Krisnadwipayana, Jakarta, Indonesia)
 Fathurrahman Ramadhani (Universitas Krisnadwipayana, Jakarta, Indonesia)

(*) Corresponding Author

DOI: http://dx.doi.org/10.30865/mib.v5i2.2841

Abstract

The process of manually prescribing drugs by doctors can cause several problems, including doctors not knowing what drugs are available and it takes time to find out what drugs are available in the pharmacy. Speech recognition is now widely used in various ways, which can help facilitate work. The application of speech recognition can be done in the e-prescribing application with the neural network method using the Convolutional Neural Network (CNN) algorithm, which is the basic method of deep learning. This study aims to facilitate physicians in filling out drug data in e-prescribing applications using speech recognition. The data used in this study were obtained from the open source dataset provided by Google and collected independent datasets. From the results of experiments that have been carried out, the accuracy achieved with 40 epochs and 40 direct impressions with different words is 90%. Where words are successfully recognized 36 words out of 40 words

Keywords


Prescription Drugs; Electronic Prescription Application; Speech Recognition; Convolutional Neural Network; Dataset

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