Skripsi

KLASIFIKASI TULISAN AKSARA BRAHMI MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK ARSITEKTUR VGG16

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Penilaian

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Many Indonesians have difficulty reading and learning the Brahmi script. Solving these problems can be done by developing software. Previous research has classified the Brahmi script but has not had an output that matches the letter. Therefore, letter classification is carried out as part of the process of recognizing Brahmi script. This study uses the Convolutional Neural Network (CNN) method with the VGG16 architecture for classifying Brahmi script writing. Training results from various amounts of image data are called model. The requested image data is a 224x224 binary image. This study has the highest quality, accuracy is 96%, highest recall is 98% and highest precision is 98%

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2107004079	T61944	T619442021	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T619442021

Publisher

Indralaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2021

Collation

xviii, 50 hlm,: ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.220 7

Content Type

Text

Media Type

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Carrier Type

-

Edition

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Subject(s)

Arsitektur Komputer
Prodi Teknik Informatika

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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