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.