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    https://repository.unej.ac.id/xmlui/handle/123456789/128453Full metadata record
| DC Field | Value | Language | 
|---|---|---|
| dc.contributor.author | WISNU, Yoga Satria | - | 
| dc.date.accessioned | 2025-10-27T05:00:57Z | - | 
| dc.date.available | 2025-10-27T05:00:57Z | - | 
| dc.date.issued | 2024-01-24 | - | 
| dc.identifier.nim | 191910201085 | en_US | 
| dc.identifier.uri | https://repository.unej.ac.id/xmlui/handle/123456789/128453 | - | 
| dc.description | Finalisasi oleh Taufik Tgl 27 Oktober 2025 | en_US | 
| dc.description.abstract | Stroke is a degenerative disease that causes damage to brain cells, disrupting the functions of organs controlled by the brain. Fragmentation or blockage of blood vessels that impede blood flow to the brain is the primary cause of stroke. In Indonesia, stroke is the second leading cause of death in individuals above 60 years old and ranks third worldwide. Globally, this disease is also a major cause of physical disabilities. Therefore, many stroke patients depend on wheelchairs for mobility. According to data from the Ministry of Social Affairs (Kemensos), in 2021 there were 209,604 people with disabilities in Indonesia due to accidents, old age, or diseases such as stroke (SIMPD). Disabilities now represent 15% of the world's population. Automatic wheelchair controls represent advancements in technology in the fields of robotics and medicine. Sensors such as distance and speed sensors are applied to enhance the functionality and safety of wheelchairs. However, the most promising development is the use of EEG (Electroencephalography) sensors that detect electrical signals from the brain to control wheelchairs, especially in severe stroke patients. | en_US | 
| dc.language.iso | other | en_US | 
| dc.publisher | Fakultas Teknik | en_US | 
| dc.subject | EGG | en_US | 
| dc.subject | STROKE | en_US | 
| dc.subject | AUTOMATIC WHEELCHAIR | en_US | 
| dc.subject | ARTIFICIAL INTELLEGENT | en_US | 
| dc.title | Rancang Bangun Sistem Kontrol Navigasi untuk Gerak Kursi Roda Berbasis EEG dengan Menggunakan Metode CNN dan Transformer | en_US | 
| dc.type | Skripsi | en_US | 
| dc.type | Software | en_US | 
| dc.identifier.prodi | S1 Teknik elektro | en_US | 
| dc.identifier.pembimbing1 | Ali Rizal Chaidir S.T., M.T. | en_US | 
| dc.identifier.pembimbing2 | Ir.Khairul Anam S.T.,M.T.,Ph.D.,IPM, ASEAN Eng | en_US | 
| dc.identifier.validator | Taufik | en_US | 
| dc.identifier.finalization | Taufik | en_US | 
| Appears in Collections: | UT-Faculty of Engineering | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| doc.pdf Until 2030-01-01  | 1.77 MB | Adobe PDF | View/Open Request a copy | 
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