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All Journal Infotek : Jurnal Informatika dan Teknologi
Hidayat, Muh.Adrian Juniarta
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Computer Science & IT Control & Systems Engineering Engineering

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Pengembangan Model AI Menggunakan Algoritma Intensity Of Character (IoC) dan Reduced Support Vector Machine (RSVM) untuk Transliterasi Citra Aksara Sasak Samsu, Lalu Muhammad; Hidayat, Muh.Adrian Juniarta; Bagja, Amir; Saiful, Muhammad
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 2 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i2.31124

Abstract

The limited human resources who are able to read Sasak script palm leaves are the main motivation for developing a transliteration tool for Sasak script images on palm leaves. By using the Reduced Support Vector Machine or RSVM algorithm as one of the classification methods, transliteration efforts can be facilitated with maximum results. The principle of the RSVM method in classifying objects by separating two different classes using a hyperplane has been proven to be able to produce maximum accuracy performance in this study. The research data in the form of Sasak script images resulting from the palm leaf image segmentation process that has been divided into 18 classes. The feature extraction algorithm used is Intensity of Character (IoC) with window sizes of 3x3, 4x4, and 5x5 and 3-Fold, 5-Fold, 7-Fold data Imbalance. The test results at the RSVM classification stage using the Linear Kernel, Polynomial Kernel,  Radial Basic Function (RBF) and One against One modeling on the 18 classes tested, where each class contains 20 handwritten Jejawen Sasak script image data on palm leaves, were recorded to produce the highest accuracy, which was 93.6%.
Co-Authors Amir Bagja Muhammad, Saiful Samsu, Lalu Muhammad