The Balinese script is a valuable cultural heritage. However, in recent decades, the use of Balinese script has significantly declined, especially among the younger generation. This is due to several factors, including the influence of technology and the lack of effective educational resources. The development of information and communication technology has supported the younger generation to communicate with each other online. Therefore, the younger generations are more interested in communicating by using technology instead of handwriting. However, it is possible to integrate handwriting and technology using handwriting recognition. The purpose of this study is to develop handwriting recognition in writing Balinese especially for young learners. Handwriting recognition in writing Balinese brings many advantages including reducing paper waste. Handwriting recognition also motivates young learners to practice handwriting using digital writing instruments on mobile devices, laptops, or desktops. This study developed handwriting recognition in a web-based application using the Bootstrap framework and employing the Jaccard Similarity and Pearson Correlation Coefficient algorithms. The sample data used are the Balinese script characters ha, na, ca, ra, ka, da, ta, and sa, collected from 10 young learners. The accuracy comparison results of the two algorithms are JS algorithm = 0% and PCC algorithm = 79%. The contributions of this research are: (1) the design of a web-based Balinese script learning system integrated with handwriting recognition technology; and (2) the application of Jaccard Similarity and Pearson Correlation Coefficient algorithms for handwriting recognition evaluation.