<![CDATA[Traditional Javanese gamelan music, particularly its songs, is an integral part of Indonesian culture and identity. However, gamelan music notation remains manual, disorganized, and difficult to access. This poses challenges to balanced education, community sustainability, and digital preservation. This study introduces an automated data extraction and gamelan notation transcription process for transforming Javanese gamelan notation in PDF format into a structured CSV. The innovation process involves parsing PDF-based Kepatihan notation, symbol-to-number conversion, musical section recognition (e.g., buka, lagu, suwuk), and organization in gatra units—each of four melodic notes. The process produces detailed metadata, such as song title, tuning (laras), mode (pathet), and gendhing classification. To evaluate extraction accuracy, the validation period also included a comparison of the converted gatra with the original PDF. The results show that the system achieved 100% accuracy on a sample size of 10 gatra and reduced processing time by 97.5% compared with manual methods. The completed dataset consists of 31 gendhing songs, providing an analyzable and scalable collection for future musicological research and education training. This study contributes to the fields of Music Information Retrieval (MIR) and Digital Humanities by enabling the efficient, standardized digitization of historical music notation. This structured dataset empowers the development of automatic notation generators, making inclusive learning tools accessible to novices and facilitating the documentation of cultural heritage through technology.]]>
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