KLASIFIKASI TULISAN AKSARA BRAHMI MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK ARSITEKTUR VGG16

VINCEN, VINCEN and Samsuryadi, Samsuryadi and Rizqie, M. Qurhanul (2021) KLASIFIKASI TULISAN AKSARA BRAHMI MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK ARSITEKTUR VGG16. Undergraduate thesis, Sriwijaya University.

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Abstract

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%.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Aksara Brahmi, Deep Learning, Convolutional Neural Network, VGG16
Subjects: Q Science > Q Science (General) > Q300-390 Cybernetics > Q325.5 Machine learning
Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions: 09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User: S.Kom Vincen Vincen
Date Deposited: 21 Jan 2022 05:44
Last Modified: 21 Jan 2022 05:44
URI: http://repository.unsri.ac.id/id/eprint/61944

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