Donni S. Silalahi, . (2020) PENERJEMAHAN BAHASA DAERAH BERBASIS GAMBAR MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Indonesia and tribal diversity are two things that cannot be separated. Therefore, keeping the tribes in Indonesia must be done by each citizen. An effort to continuously maintain a tribe is to ensure the preservation of its local language. Local language is increasingly rarely used because it is considered an ancient language and still lack of means to access the local languages. In this study, would design a system to translate an image containing Indonesian language text into a local language text. This research will go through several stages, starting from the pre-process stage, segmenting the character in the image using the labeling by Connected Component Analysis, then classifying the character using the Convolutional Neural Network method. After that, all the characters will be merged into a text and then translate it. At this stage of translation, will use the help of the Levenshtein algorithm to match the text of the classification result with the text in the local language dictionaries. This research is expected to be able to translate the Indonesian text in the form of image into local language text, so it will give someone access to know the local language and want to preserve it.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 1610511063] [Pembimbing 1: Anita Muliawati] [Pembimbing 2: Mayanda Mega Santoni] [Penguji 1: Henki Bayu Seta] [Penguji 2: Noor Falih] |
| Uncontrolled Keywords: | local language, connected component analysis, convolutional neural network, levenshtein algorithm, local language translation |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General) |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | Donni S Silalahi |
| Date Deposited: | 12 Jan 2022 05:15 |
| Last Modified: | 12 Jan 2022 05:15 |
| URI: | http://repository.upnvj.ac.id/id/eprint/7064 |
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