Pengenalan Pola Tulisan Tangan Aksara Bima menggunakan Ciri Tekstur dan KNN: Handwriting Recognition of Bima Script using Texture Features and KNN - Fitri Bimantoro; Arik Aranta; Gibran Satya Nugraha; Ramaditia Dwiyansaputra; Ario Yudo Husodo (Informatics Engineering Dept., Faculty of Engineering, University of Mataram, 2021)
As the fact, that is Bima script did not familiar to bimanese, Bima script as a cultural heritage needs to be preserved. Pattern recognition has been used to recognize several of ancient script. Gray Level Co-occurence Matrix (GLCM) as features exctraction and K Nearest Neighbour (KNN) as a classifier show the good performance to recognize of an ancient script. so, in this research we use GLCM and KNN to recognize Bima script. we use 2640 images of handwritting bima Script that is collected from 10 volunter. Each volunter write 22 of Bima script twelve times each script. The experimental result show that the performance of our model is good enough, with 60.86% of accuracy that is obtained by manhattan distances.