Abstract
<p class="0abstract">the rapid development of mobile technologies allows platform devices to perform sophisticated tasks, including character recognition. These identification systems are notable techniques that required high computation cost, in order to achieve acceptable accuracy resulting from diversity in alphabet shape and method of writing, especially for the non-Latin alphabet, e.g., Javanese letter. In addition, numerous studies have attempted to address these issues by employing a Convolution Neural Network (CNN) due to its ability to provide high accuracy in character detection. However, the performance on mobile devices is possibly faced with problems resulting from the limitation of computation resource on the platform that also affect computation cost. This study, therefore, proposes a 2-tier architecture by placing the mobile app as a client that invokes a Javanese letters classifier service, which is based on CNN, and implemented in the web-server through the Application Program Interface (API). The results show that the letter classification was successfully implemented in a mobile platform, with an accuracy rate of 86.68%, utilizing training for 50 epochs, and an average time of 1935 ms.</p>
Highlights
The use of classification image as a part of pattern recognition and machine learning has recently become an exciting topic
A major challenge in this development is related to the cost sacrificed for mobile computation resource, numerous scholars attempted techniques that are capable of resolving the problem, including Deep Learning, which encompasses Convolution Neural Network (CNN)
This section discusses the concept of interface Application Program Interface (API) and mobile client-server architecture in the building of a Javanese letter classifier, which was subsequently divided into two parts:
Summary
The use of classification image as a part of pattern recognition and machine learning has recently become an exciting topic. According to [7], children tend to be interested in an application that offers both educational aspects and entertainment, the integration of engaging content and the advantages of smartphone features, tends to motivate the user to engage with the app, enhancing its perception as a productive tool in the process of learning about a specific subject [7] [8] This enhances the potential of adopting character recognition as an entertainment element, with content that are engaging, possessing the tendency of attracting and encouraging students to learn particular topic related to alphabetic principle [5]. The alternative approach needs to be observed, in order to ensure smooth and accurate operation in a mobile platform
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