Thariqhat Rama Putra, . (2023) KLASIFIKASI GERAKAN BELA DIRI PENCAK SILAT MENGGUNAKAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK BERBASIS WEBSITE. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
The result of human actions learned and organized within a society is referred to as culture. One of the cultures within society is the martial art of Pencak Silat, which has been passed down through generations by the Indonesian community. Culture has three forms, and Pencak Silat falls under the form of martial arts culture, which has its own patterns and behaviors. Pencak Silat is considered a concrete activity that can be observed and is performed by individuals within the community. One of the methods used in this research is the convolutional neural network algorithm, which is inspired by the visual cortex of mammals and its simple and complex cells. Convolutional neural network is chosen as the method in this research because of its classification capabilities specifically designed for image data. The testing is conducted by collecting data from Pencak Silat martial arts practitioners, followed by preprocessing and digital image classification using the convolutional neural network algorithm. The classification results are saved with the .h5 extension and will be implemented in a website-based application, aiming to serve as a model for recognizing Pencak Silat martial arts movements.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No. Panggil : 1910511082] [Pembimbing : Bayu Hananto] [Penguji 1 : Yuni Widiastiwi] [Penguji 2 : Kraugusteeliana] |
| Uncontrolled Keywords: | Culture, Pencak Silat, Convolutional Neural Network, Website, Digital Image |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | Thariqhat Rama Putra |
| Date Deposited: | 31 Jul 2023 03:01 |
| Last Modified: | 31 Jul 2023 03:01 |
| URI: | http://repository.upnvj.ac.id/id/eprint/26222 |
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