Sequence Chunking on Quran in English Translation using Bidirectional Long Short-Term Memory
TRY ARIE RAHMAT INSANI
Informasi Umum
Kode
20.04.3747
Klasifikasi
000 - General Works
Jenis
Karya Ilmiah - Skripsi (S1) - Reference
Subjek
Computer Science
Dilihat
32 kali
Informasi Lainnya
Abstraksi
Every Moslem is obliged to read and understand the meanings of the Quran. The problem is the amount of information contained in the Quran so that ordinary people have difficulty understanding the Quran as a whole. Neural networks can be used to extract important information in the Quran to solve this problem. Therefore, the author proposes a model to identify and classify tags using sequence chunking. The system will use the Bi-LSTM model where the system will be given various token from the Quran as the inputs to be identified as the correct tags. The author is using the dataset obtained from website quran.com. The evaluation of the proposed model produces an f-measure value of 0.903.
Koleksi & Sirkulasi
Seluruh 1 koleksi sedang dipinjam
Anda harus log in untuk mengakses flippingbook
Pengarang
| Nama | TRY ARIE RAHMAT INSANI |
| Jenis | Perorangan |
| Penyunting | Moch. Arif Bijaksana |
| Penerjemah |
Penerbit
| Nama | Universitas Telkom |
| Kota | |
| Tahun | 2020 |
Sirkulasi
| Harga sewa | IDR 0,00 |
| Denda harian | IDR 0,00 |
| Jenis | Non-Sirkulasi |
