Modelling Naïve Bayes for Tembang Macapat Classification

The tembang macapat can be classified using its cultural concepts of guru lagu, wilangan, and gatra. People may face difficulties recognizing certain songs based on the established rules. This study aims to build classification models a simple yet powerful Naïve Bayes classifier. Naive generate high-accuracy values from sparse data. modifies concept Guru Lagu by retrieving last vowel each line. At same time, wilangan’s guidelines are amended counting number all characters (Model 2) rather than calculating syllables 1). data source is serat wulangreh with 11 types macapat, namely maskumambang, mijil, sinom, durma, asmaradana, kinanthi, pucung, gambuh, pangkur, dandhanggula, megatruh. k-fold cross-validation used evaluate performance 88 result shows that proposed Model 1 performs better 2 in classification. promising method opens potential mining engine as teaching preservation media.