Segmentasi Aksara Pada Tulisan Aksara Jawa Menggunakan Adaptive Threshold

Arifianto, Teguh (2016) Segmentasi Aksara Pada Tulisan Aksara Jawa Menggunakan Adaptive Threshold. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Penelitian mengenai Aksara Jawa sudah banyak digunakan. Salah
satunya adalah penelitian mengenai naskah pada Aksara Jawa. Kondisi naskah
Aksara Jawa sebagian besar dalam kondisi baik meskipun masih terdapat
beberapa halaman yang robek dan warna kertas yang memudar. Hal ini
disebabkan karena umur kertas yang sudah puluhan tahun lebih dan bahan kertas
yang kurang baik.
Penelitian ini difokuskan hanya untuk membagi aksara pada citra tulisan
tangan menjadi karakter-karakter aksara yang dapat digunakan dalam pengenalan
Aksara Jawa pada penelitian selanjutnya. Penelitian ini terdapat lima proses, yaitu
akuisi citra, proses preprocessing, proses segmentasi, dilasi, dan pelabelan
Aksara. Pada proses segmentasi, penelitian ini menggunakan adaptive threshold.
Metode adaptive threshold dapat digunakan pada segmentasi citra
Aksara Jawa karena metode ini memilih nilai threshold berdasarkan variasi
intensitas tiap lokal window. Hasil nilai akurasi yang didapat dari penelitian ini
yaitu sebesar 88.60% dari 30 data citra Aksara Jawa.

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Research on character java there have been many used. One of them is
research on manuscript in character java. The condition manuscript character java
mostly in good condition although there is still several pages torn and color paper
faded. This is because age paper already dozens of more years and materials paper
a less well.
Research is focused only to divide character in image handwriting be the
characters characters that can be used in the introduction of character java in the
next research. This research there are five the process, image aquatition, the
preprocessing, the process segmentation, dilations, and the labeling character. To
the process segmentation, this research using adaptive threshold.
A method of adaptive threshold can be used on segmentation image
character java because this method choose threshold value based on variations in
intensity every local window. The results of value accuracy obtained from the
study is as much as 88.60% of 30 image data character java.

Item Type: Thesis (Masters)
Additional Information: RTE 006.425 Ari s
Uncontrolled Keywords: Aksara Jawa; segmentasi; adaptive threshold; Character java; segmentation; adaptive threshold
Subjects: Z Bibliography. Library Science. Information Resources > Z004 Books. Writing. Paleography
Divisions: Faculty of Industrial Technology > Electrical Engineering > 20101-(S2) Master Thesis
Depositing User: Anis Wulandari
Date Deposited: 29 May 2017 02:28
Last Modified: 26 Dec 2018 04:00
URI: http://repository.its.ac.id/id/eprint/41389

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