Design and Building Javanese Script Classification in The State Museum of Sonobudoyo Yogyakarta
Abstract
The Sonobudoyo State Museum is one of the state museums in Yogyakarta where stores historical objects like the Javanese script. This Javanese script presents in street names, especially in the city of Yogyakarta to represent local content for elementary, middle, and high schools. To read and understand Javanese script, people must learn it within a specified period, whereas with Latin letters are easier and faster to understand. The purpose of this paper is to design and build a Javanese script classification dataset to attract both adults, children, and parents as effective learning media. We construct the dataset by using Deep Learning with the Convolutional Neural Network (CNN). Stages of making a dataset are input data, the process of building models, and training can then recognize Javanese script images. We collect the dataset from the internet and several different people to train computer machines. In this paper, we construct the Javanese script classification dataset to help users to detect Javanese characters. The results of this training the application of Javanese script classification can produce a certain level of recognition of Javanese script patterns in a real application.
Downloads
IJICOM is an open-access journal. Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.