PENERAPAN KLASIFIKASI MENGGUNAKAN ALGORITMA ARTIFICIAL NEURAL NETWORK (ANN) DENGAN FEATURE SELECTION RANDOM FOREST UNTUK MENGETAHUI FAKTOR-FAKTOR PENYEBAB KECELAKAAN LALU LINTAS

Darnisa Azzahra Nasution, . (2020) PENERAPAN KLASIFIKASI MENGGUNAKAN ALGORITMA ARTIFICIAL NEURAL NETWORK (ANN) DENGAN FEATURE SELECTION RANDOM FOREST UNTUK MENGETAHUI FAKTOR-FAKTOR PENYEBAB KECELAKAAN LALU LINTAS. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

Traffic accident is an unexpected event, then involving motorists, vehicles with other road users or not, resulting in loss of property to human victims. Currently, traffic accidents are a significant source of death in Indonesia, so actions are needed to reduce or even prevent accidents. This research was conducted to apply the classification of Artificial Neural Network (ANN) algorithm with Random Forest as a technique for feature selection in knowing the causes of traffic accidents based on accident rates, which can later help provide information to the public. The results obtained are the classification with feature selection produces an accuracy of 75.17%, which slightly increases compared to the absence of feature selection, which is 75.14%. The factors that cause top traffic accidents based on tests that have been done are GPS-latitude coordinates and GPS-longitude coordinates.

Item Type: Thesis (Skripsi)
Additional Information: [No.Panggil: 1610511077] [Pembimbing 1: Iin Ernawati] [Pembimbing 2: Nurul Chamidah] [Penguji 1: Yuni Widiastiwi] [Penguji 2: Bambang Tri Wahyono]
Uncontrolled Keywords: Traffic Accident, Random Forest, ANN
Subjects: T Technology > T Technology (General)
Divisions: Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User: Darnisa Azzahra Nasution
Date Deposited: 13 Jan 2022 02:02
Last Modified: 13 Jan 2022 02:02
URI: http://repository.upnvj.ac.id/id/eprint/6833

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