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. ====================================================================================== 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) |
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| 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: | Mrs Anis Wulandari |
| Date Deposited: | 29 May 2017 02:28 |
| Last Modified: | 26 Dec 2018 04:00 |
| URI: | https://repository.its.ac.id/id/eprint/41389 |
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