Skripsi

KLASIFIKASI CITRA AKSARA HIRAGANA KUZUSHIJI MENGGUNAKAN SUPPORT VECTOR MACHINE (SVM)

---

Kuzushiji is a cursive writing style used in various classical Japanese manuscripts. Over time, this script has become difficult for modern readers to interpret. This condition encourages the need for research on the automatic classification of characters written in this style to support the study and understanding of classical Japanese texts. This study applies the Support Vector Machine (SVM) method to classify images of Hiragana Kuzushiji characters. Feature extraction is performed using the Histogram of Oriented Gradients (HOG) method to capture shape characteristics, while Principal Component Analysis (PCA) is used to reduce feature dimensions and improve training efficiency. The SVM model is evaluated using three kernel types: Linear, Sigmoid, and Radial Basis Function (RBF). The experimental results show that the RBF kernel with parameters C=10 and gamma=0.04 achieves the best performance, with accuracy of 0.90, precision of 0.90, recall of 0.88, and F1-score of 0.89.

---

Availability

Detail Information

Series Title

-

Call Number

T1903442025

Publisher

Indralaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2025

Collation

xv, 126 hlm.; ilus.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

-

Classification

006.320 7

Content Type

Text

Media Type

-

Carrier Type

-

Edition

-

Subject(s)

Support Vector Machine (SVM)
Prodi Teknik Informatika

Specific Detail Info

-

Statement of Responsibility

MI

Other version/related

File Attachment

Comments

---

You must be logged in to post a comment