Recognition of the Lima Pandawa Shadow Puppet characters utilizing Principal Component Analysis (PCA) for feature extraction and K-Nearest Neighbor (KNN) for classification
DOI:
https://doi.org/10.24002/ijis.v8i1.11032Abstract
The traditional type of puppet-shadow play, Wayang Kulit, is an integral component of Indonesian culture. The Pandawa Lima, protagonists in this artistic medium, have great importance not just in narrative but also in embodying moral and ethical principles. The automated identification of these characters can optimize a range of applications, such as instructional resources, digital preservation, and interactive displays. This research intends to maximize the advantages of PCA and KNN by utilizing their respective strengths: PCA's capacity to decrease data dimensionality and KNN's efficacy in classification tasks. An expected outcome of this combination is an enhancement in recognition accuracy without compromising computational efficiency. The classification matrix indicates that the model achieved a 78% accuracy rate. Class-specific accuracy, recall, and F1-scores are as follows: arjuna achieves a precision of 0.85, recall of 0.91, and F1 Score of 0.87. Macro averages for precision, recall, and F1 are 0.77, 0.76, and 0.74, respectively. Weighted averages for these metrics are 0.80, 0.78, and 0.77, respectively. The model exhibits strong performances on Arjuna, Sadewa, and Yudistira, but encounters difficulties with Bima and Nakula.
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