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Journal of Engineering and Applied Sciences
Year: 2019  |  Volume: 14  |  Issue: 19  |  Page No.: 6982 - 6990

Design of arabic recognition application using Convolutional neural network

Salma asti Shofia Rosyda, Budhi Irawan and Anggunmeka Luhur Prasasti    

Abstract: Arabic is one of the languages which attracted, needed and used by a lot of people in the world. Many countries have used Arabic language in courses which related to the international world. Arabic also used by Muslim people, beacause Arabic is the main language of the hooly book of Muslim (Quran). The importance to know and to understand the basic of Arabic language for the temporary needs like when we travel to a country which use Arabic as their main language include during Hajj and Umrah. At this time the smartphone has become a major need for humans, based on that then made Arabic writing recognition application which aims to help pilgrims of Hajj and Umrah who can not speak Arabic. In this study, the method used is the method of Convolutional Neural Network (CNN). Test results from Arabic handwritten image classification using CNN resulted in an average accuracy of 60%. It can be concluded that the CNN method used in this application is able to do a good classification.

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