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All Journal Blend Sains Jurnal Teknik Al'Adzkiya International of Computer Science and Information Technology Journal
Raihan, Elza Ahmad
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Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Pemanfaatan Sistem Informasi dalam Pemesanan serta Digitalisasi Tiket Bus Berbasis Website Batubara, Ismail Hanif; Raihan, Elza Ahmad; Tanjung, Muhammad Iqbal; Fadlurohman, Dimas; Can, Alvita
Blend Sains Jurnal Teknik Vol. 1 No. 1 (2022): Edisi Juli
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (319.597 KB) | DOI: 10.56211/blendsains.v1i1.73

Abstract

Dalam dunia bisinis , umumnya pengguna serta pemilik dari perusahaan memerlukan suatu hal yang inovatif untuk membantu menunjang kinerja serta mempermudah penggunaan ataupun pencarian tentang data sebuah produk. Hadirnya internet berbasis website ini akan mempermudah seluruh kalangan untuk dapat mengakses segala bentuk informasi termasuk memanfaatkan media tersebut untuk dapat menghubungkan hubungan antara pelanngan serta produik perusahaan tersebut yaitu salah satunya pemesenan tiket bus. Berdasarkan berbagai kemudahan dan kegunaanya yang dimilki oleh internet tersebut maka dikembangkan sebuah “Pemanfataan Sistem Informasi dalam Pemesenan serta Digitalisasi Tiekt Bus Berbasis Website”. System ini dibuat dengan perangkat lunak PHP, MySQL dan Bootstrap. Sistem Informasi ini dirancang agar dapat memberikan kemudahan dalam hal pelayanan pemesanan tiket dan memperoleh informasi lain yang dibutuhkan oleh pelanggan
Convolutional Neural Network Based Human Posture Correction Implementation for Yoga Health Motion Classification Raihan, Elza Ahmad
Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 5, No 1 (2024)
Publisher : Al'Adzkiya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55311/aiocsit.v5i1.316

Abstract

Post-pandemic lifestyle patterns have undergone many changes with the implementation of digital transformation, one of which is the meditation pattern such as yoga practice that can be done independently at home without direct interaction with the instructor. This study also aims to develop a yoga movement classification system using Convolutional Neural Network (CNN) based on human posture correction. Using the Movenet model, this system can recognise and classify different yoga poses to provide accurate feedback on correct posture. Training data was collected from yoga photographs and processed into pose images that were analysed using CNN. The results of this study indicate that the developed system is able to achieve a high level of accuracy in identifying yoga poses, which has the potential to help users improve their posture and reduce the risk of injury. This system is also implemented in a mobile application, making it easier for users to access posture correction in real time. As such, this research makes a significant contribution to the fields of health and technology by providing innovative solutions for safer and more effective yoga practice.
Co-Authors Can, Alvita Fadlurohman, Dimas Ismail Hanif Batubara Tanjung, Muhammad Iqbal