TIMORREMBOKO, FARRAS (2020) IMPLEMENTASI JARINGAN SYARAF TIRUAN PADA KENDALI LAMPU SOROT MOBIL ADAPTIF BERBASIS PYTHON. S1 thesis, Universitas Mercu Buana Bekasi.
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Abstract
ABSTRAK Fungsi utama dari lampu jalan untuk memastikan keamaan manusia. Penerangan lalu lintas diharuskan memberikan kondisi visibilitas yang baik dan mengurangin potensi bahaya dengan menerangi objek di sepanjang jalan. Jaringan Syaraf Tiruan diharapkan menghasilkan model terbaik untuk mengendalikan intensitas lampu sorot mobil adaptif pada kondisi yang sesuai dengan lapangan yaitu kondisi terang, mendung dan malam hari. Data diperoleh dari alat bantu yang terdiri dari 5 buah sensor cahaya dan 2 buah LED. Model terbaik didapat melalui training beberapa bentuk model Jaringan Syaraf Tiruan dan prediksi intensitas cahaya lampu sorot mobil berdasarkan dataset training dan testing. Training dilakukan pada 12 model berbeda dengan merubah banyak neuron hidden layer dan fungsi aktivasi pada program Jaringan Syaraf Tiruan. Model Jaringan Syaraf Tiruan terbaik memiliki parameter 20 node hidden layer, fungsi aktivasi Relu dan epoch 200 dengan error training sebesar 0,0038 dan hasil error prediksi sebesar 147,12. Kata Kunci : Jaringan Syaraf Tiruan, Komputer, Sensor Cahaya, LED, Kendali ABSTRACT The main function of headlight is to ensure human security. Traffic light is required to provide good visibility conditions and reduce potential hazards by illuminating objects along the road. Artificial Neural Network is expected to produce the best model to control the intensity of adaptive headlight in various condition, such as day hour, cloudy, and night hour. Data was obtained from 5 light sensors and 2 LEDs. Best model was produced from training several model and predicting the intensity of headlight based on training and predicting dataset. Training was carried out on 12 different models by changing amount of neuron hidden layer and activation function at Artificial Neural Network code. Artificial Neural Network best model has 20 nodes at hidden layer, Relu as activation function and 200 epochs with training error is 0.0038 and prediction error is 147.12. Keyword :Artificial Neural Network, Computer, Light Sensor, LED, Control.
| Item Type: | Thesis (S1) |
|---|---|
| Call Number CD: | FE/ELK 20 040 |
| NIM/NIDN Creators: | 41418320045 |
| Uncontrolled Keywords: | Kata Kunci : Jaringan Syaraf Tiruan, Komputer, Sensor Cahaya, LED, Kendali |
| Subjects: | 600 Technology/Teknologi > 620 Engineering and Applied Operations/Ilmu Teknik dan operasi Terapan > 621 Applied Physics/Fisika terapan > 621.3 Electrical Engineering, Lighting, Superconductivity, Magnetic Engineering, Applied Optics, Paraphotic Technology, Electronics Communications Engineering, Computers/Teknik Elektro, Pencahayaan, Superkonduktivitas, Teknik Magnetik, Optik Terapan, Tekn |
| Divisions: | Fakultas Teknik > Teknik Elektro |
| Depositing User: | siti maisyaroh |
| Date Deposited: | 16 Jun 2022 02:17 |
| Last Modified: | 16 Jun 2022 02:17 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/63441 |
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