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Unjuk kerja k-nearest neighbor untuk alihaksara citra aksara Nusantara

K-nearest neighbor performance for Nusantara scripts image transliteration

Department of Informatics, Universitas Sanata Dharma, Indonesia

Received: 23 Aug 2019; Revised: 28 Feb 2020; Accepted: 13 Mar 2020; Available online: 20 Mar 2020; Published: 30 Apr 2020.
Open Access Copyright (c) 2020 Jurnal Teknologi dan Sistem Komputer
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Citation Format:
The concept of classification using the k-nearest neighbor (KNN) method is simple, easy to understand, and easy to be implemented in the system. The main challenge in classification with KNN is determining the proximity measure of an object and how to make a compact reference class. This paper studied the implementation of the KNN for the automatic transliteration of Javanese, Sundanese, and Bataknese script images into Roman script. The study used the KNN algorithm with the number k set to 1, 3, 5, 7, and 9. Tests used the image dataset of 2520 data. With the 3-fold and 10-fold cross-validation, the results exposed the accuracy differences if the area of the extracted image, the number of neighbors in the classification, and the number of data training were different.
Keywords: classification; KNN algorithm; transliteration; Nusantara script image
Funding: Universitas Sanata Dharma under contract 042/LPPM USD/V/2019

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