Character Recognition of Handwriting of Javanese Character Image using Information Gain Based on the Comparison of Classification Method

Indonesia is a country rich in variety of regional cultures. Regional airspace needs to be preserved so as not become extinct. One them the local culture Central Java Province, namely Javanese Character. In this modern era, globalization growing every country. The impact increasingly widespread and developing society. effect people prefer foreign language skills learn languages. This study, applies method character recognition using new combination workflow that contains Local Binary Pattern (LBP) Information Gain. Then compare Support Vector Machine (SVM), k-Nearest Neighbor Naïve Bayes. LBP used obtain an image's texture or shape characteristics. Gain for feature selection algorithm, whereas SVM, ayes classification method. From previous research, information gain succeeded increasing accuracy by 2%. research compares SVM with another method, result shows our proposed can improve performance. best gets 87,86%, at ten folds cell size 64x64.