Muhammad Akbar Pratama Putra, . (2024) KLASIFIKASI CITRA API DAN BUKAN API DENGAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK 1 DIMENSI DAN YOLO. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Fire is a phenomenon that causes many physical and material losses. It’s difficult to predict the initial cause of the fire and where the fire occurred. With the problems obtained, this research aims to carry out fire detection based on images to determine the presence of a fire. Related research regarding fire and not fire classification based on images has been carried out using 2-dimensional Convolutional Neural Network algorithm with good final results. Fire detection based on images will be carried out by creating an algorithm model with 1 Dimension Convolutional Neural Network and pretrained model YOLOv8. This research contain interface display as input media using Tkinter library. Results for algorithm model using 1 Dimension Convolutional Neural Network is 88.43% for accuracy, precision and recall. The result for pretrained model YOLOv8 is 0,722 and 0,632 for precision and recall. The actual understanding of the input data is still low in classification whether there is a fire or not based on images and requires other processing processes for the image data.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 2010511040] [Pembimbing: Neny Rosmawarni] [Penguji 1: Indra Permana Solihin] [Penguji 2: Muhammad Adrezo] |
| Uncontrolled Keywords: | Fire, Convolutional Neural Network, YOLO, Interface |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | Muhammad Akbar Pratama Putra |
| Date Deposited: | 22 Jan 2024 03:27 |
| Last Modified: | 20 Feb 2024 03:30 |
| URI: | http://repository.upnvj.ac.id/id/eprint/28233 |
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