Farel Fathurrahman, . (2020) KLASIFIKASI CITRA TEKS UNTUK PENERJEMAHAN BAHASA DAERAH MENGGUNAKAN ARTIFICIAL NEURAL NETWORK. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Local language are used to communicate with each other in certain areas. Many factors make the young generation's awareness to preserve the local language. One of them is still lack of means to access the local languages, so this is one of the problems that occurs. In this study, would design a translation system of an image containing Indonesian text into a local language text. This research starts from the pre-process stage, character segmentation techniques in the image using Connected Component Analysis labeling. After that, the image is extracted then the character image is classifying using the Artificial Neural Network method. The next step is to merge characters into a text. After that, the translation process uses the Levensthein algorithm to match the results of the text classification with local language. This research is expected to be able to translate the image of Indonesian texts into local language text, to help preserve local language in Indonesia.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No. Panggil: 1610511083] [Pembimbing 1: Anita Muliawati] [Pembimbing 2: Mayanda Mega Santoni] [Penguji 1: Henki Bayu Seta] [Penguji 2: Artambo B. Pangaribuan] |
| Uncontrolled Keywords: | local language, cca, artificial neural network, local language translation |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | Farel Fathurrahman |
| Date Deposited: | 12 Jan 2022 05:29 |
| Last Modified: | 12 Jan 2022 05:29 |
| URI: | http://repository.upnvj.ac.id/id/eprint/7285 |
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