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All Journal Jurnal Cakrawala Informasi (JCI)
Nurdianto, Kristiawan
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Computer Science & IT Decision Sciences, Operations Research & Management Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science

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Klasifikasi Gambar Aksara Jawa dengan Optimasi Parameter KNN Menggunakan GridSearchCV Priyambodo, Aji; Heses, Martius Apun; Nurdianto, Kristiawan
Jurnal Cakrawala Informasi Vol 4 No 2 (2024): Desember : Jurnal Cakrawala Informasi
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) - Institut Teknologi dan Bisnis Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jci.v4i2.525

Abstract

This study focuses on optimizing the K-Nearest Neighbors (KNN) algorithm for Javanese script classification using the Cosine Similarity metric. Through a grid search in cross-validation, the optimal combination of hyperparameters, including the number of neighbors, weighting functions, and distance metrics, was identified. The results demonstrate that the Cosine Similarity metric with a distance weighting scheme achieved the best accuracy of 99.99%. Furthermore, evaluation based on precision, recall, and f1-score revealed highly stable performance across various classes, with most achieving perfect scores. Compared to previous methods, such as LBP, CNN, and DCNN, this approach shows a significant accuracy improvement. These findings indicate that optimizing KNN with the Cosine Similarity metric is highly reliable for developing classification models for complex patterns.
Co-Authors Aji Priyambodo Heses, Martius Apun