eBaybayMo: An E-Learning Mobile Application Tool for Transliterating Baybayin Characters to Latin Letters Using k-NN Algorithm

Writing systems have played an essential role in human communication, evolving uniquely within various cultures and societies. One such writing system is Baybayin, an ancient script for writing Philippine languages that has recently rekindled interest. This study dedicates itself to developing a Baybayin Character Recognition and Transliteration mobile application that utilizes the k-Nearest Neighbors (k-NN) Algorithm. The primary objective of this mobile application is to enhance the accessibility of Baybayin by enabling users to recognize and transliterate images of fundamental Baybayin characters. Utilizing the k-NN algorithm within the API enhances accuracy through machine learning techniques. Before we make the app available to users, we will test images of primary Baybayin characters captured on mobile phones for accuracy. After assessing the machine learning model API using a 2x2 confusion matrix, it achieved an accuracy rate of 95.47%. The researchers recommend implementing the developed system in schools that teach Baybayin. Further, future researchers may conduct studies using empirical evidence and impact assessment of utilizing the developed system correlated with students' efficiency and performance.