PENGENALAN POLA TULISAN TANGAN AKSARA ARAB MENGGUNAKAN EKSTRAKSI FITUR LOCAL BINARY PATTERN DAN ZONING DAN KLASIFIKASI BACKPROPAGATION ARTIFICIAL NEURAL NETWORK

Pencarian berdasarkan :

SEMUA Pengarang Subjek ISBN/ISSN Pencarian Spesifik

Pencarian terakhir:

Tugas Akhir Informatika

PENGENALAN POLA TULISAN TANGAN AKSARA ARAB MENGGUNAKAN EKSTRAKSI FITUR LOCAL BINARY PATTERN DAN ZONING DAN KLASIFIKASI BACKPROPAGATION ARTIFICIAL NEURAL NETWORK

Farhan Yakub Bawazir - Nama Orang;

Arabic is a language that is spoken as the first or native language of more than 280 million people, most of whom live
in the Middle East and North Africa. Apart from the Middle East and North Africa, Arabic is also familiar and often used
in Indonesia because of the majority of Indonesia's population is Muslim and Arabic is the language of worship in
Islam. The recognition of Arabic handwritten letters is one of the studies that has been done before, where the
accuracy results obtained vary according to the research and methods used. This study aims to determine the accuracy
resulting from the recognition of Arabic script handwriting patterns using a combination of the DCT(Discrete Cosine
Transform) feature extraction method and the ANN Backpropagation classification method. The data used for this
study were data from handwritten sources on A4 HVS paper using markers with categories of age from 7-13 years old
and 18-23 years old with 15 respondents in each group and a total dataset image of 8400. Testing the best model
model obtained on all images produces an accuracy of 80.79%, using the images of age range 17-23 years produces
87.27% accuracy, and the images of age range 7-13 produces an accuracy of 72.84%

Ketersediaan

Tidak ada salinan data

Informasi Detail

Judul Seri: -
No. Panggil: 398.8.Far.p
Penerbit: Universitas Mataram : Fakultas Teknik Unram., 2020
Deskripsi Fisik: viii;71 Hlm; iilus;21x29 cm
Bahasa: Indonesia
ISBN/ISSN: -
Klasifikasi: 398.8
Tipe Isi: other
Tipe Media: computer
Tipe Pembawa: audio disc
Edisi: Edisi 1 Jilid 1
Subjek: POLA TULISAN TANGAN AKSARA ARAB
pengenalan pola, tulisan tangan, aksara, DCT, back
Info Detail Spesifik: PENGENALAN POLA TULISAN TANGAN AKSARA ARAB MENGGUNAKAN EKSTRAKSI FITUR LOCAL
Pernyataan Tanggungjawab: Farhan Yakub Bawazir

Versi lain/terkait

Tidak tersedia versi lain

Lampiran Berkas

PENGENALAN POLA TULISAN TANGAN AKSARA ARAB MENGGUNAKAN EKSTRAKSI FITUR LOCAL BINARY PATTERN DAN ZONING DAN KLASIFIKASI BACKPROPAGATION ARTIFICIAL NEURAL NETWORK

Komentar

Anda harus login sebelum memberikan komentar