IMPLEMENTASI DEEP LEARNING MENGGUNAKAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK GUNA MENGETAHUI KUALITAS BAN KENDARAAN

Alvin Putra Perdana, . (2024) IMPLEMENTASI DEEP LEARNING MENGGUNAKAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK GUNA MENGETAHUI KUALITAS BAN KENDARAAN. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

Nowadays, having a vehicle is a necessity that must be owned by the society to simplify traveling from the start location to the final destination. Based on data from the Central Bureau of Statistics, the latest trend regarding data on the number of motorcycles in 2021 is 120,042,298 units and data on the number of passenger car in 2021 is 16,413,348 units. As the number of vehicles on the road increases, this is inseparable from the risk of traffic accidents. The phenomenon of motorized vehicles using bald tires is still often found. Some possible accidents caused by the use of bald tires are sliding, blown tires, and vulnerable to impacts from poor road conditions. In dealing with this phenomenon, tire quality can be classified using Support Vector Machine (SVM) and Convolutional Neural Network (CNN) algorithms with ResNet50 Architecture. The data used are the data from direct acquisition in the field, with a total of 400 images divided into 2 classes. The steps start from preprocessing, feature extraction, data splitting and others. The data splitting performed is 80:20 with 320 train data. The performance obtained for the Support Vector Machine (SVM) is 87.5% with a polynomial kernel. However, after implementing Deep Learning, the performance of the model to classify vehicle tires increased to 100%.

Item Type: Thesis (Skripsi)
Additional Information: [No.Panggil: 2010511011] [Pembimbing 1: Nur Hafifah Matondang] [Pembimbing 2: M. Octaviano] [Penguji 1:Yuni Widiastiwi] [Penguji 2:Nurul Afifah Arifuddin]
Uncontrolled Keywords: Tire, Convolutional Neural Network, SVM, Deep Learning
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User: Alvin Putra Perdana
Date Deposited: 22 Jan 2024 03:46
Last Modified: 22 Feb 2024 02:07
URI: http://repository.upnvj.ac.id/id/eprint/27984

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