Damayanti, Lestari Ekky (2020) Pengenalan Tulisan Tangan Naskah Aksara Jawa Aturan Penulisan Mardi Kawi Menjadi Huruf Alfabet Pada Media Kertas Menggunakan Metode Convolutional Neural Network (CNN) Arsitektur You Only Look Once (YOLO). Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Pelestarian kebudayaan perlu dilakukan, salah satunya melestarikan bukti-bukti sejarah dalam wujud naskah. Pengenalan aksara Jawa diperlukan sebagai upaya pelestarian peninggalan kebudayaan bangsa. Dewasa ini pengenalan aksara Jawa masih menggunakan metode sederhana yaitu dengan membaca satu persatu, lalu menuliskan kembali. Pada tugas akhir ini akan dilakukan pengenalan aksara Jawa yang setiap aksaranya diambil dari gambar hasil pemindaian sebuah naskah teks media kertas dengan aturan penulisan Aksara Jawa Mardi Kawi menjadi huruf alfabet sehingga dapat diketahui bagaimana cara membacanya. Menggunakan metode Convolutional Neural Network (CNN) sebagai metose pemrosesan data
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Cultural preservation needs to be done, one of which is preserving historical evidence in the form of manuscripts. The introduction of Javanese script is needed as an effort to preserve the cultural heritage of the nation. Today, the introduction of Javanese script still uses a simple method, which is to read one by one and then rewrite it. In this final project, an introduction to Javanese script will be carried out, with each script taken from a scanned image of a paper text paper with the rules of writing Javanese script Mardi Kawi into alphabet letters so that it can be known how to read it. Using the Convolutional Neural Neural Network (CNN) method as a data processing method.
Item Type: | Thesis (Masters) |
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Additional Information: | RSKom 006.32 Dam p-1 |
Uncontrolled Keywords: | tulisan tangan, aksara Jawa aturan penulisan Mardi Kawi, Convolutional Neural Network (CNN) |
Subjects: | P Language and Literature > PN Literature (General) > PN0441 Literary History T Technology > T Technology (General) T Technology > T Technology (General) > T57.5 Data Processing |
Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Computer Engineering > 90243-(S1) Undergraduate Thesis |
Depositing User: | Damayanti Lestari Ekky |
Date Deposited: | 18 Mar 2025 07:19 |
Last Modified: | 18 Mar 2025 07:19 |
URI: | http://repository.its.ac.id/id/eprint/74591 |
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