ANALISIS MODEL CLUSTERING KECELAKAAN LALU LINTAS DI KOTA PALEMBANG MENGGUNAKAN PENDEKATAN MACHINE LEARNING BERDASARKAN DATA SEKUNDER DARI KEPOLISIAN RESOR KOTA BESAR PALEMBANG TAHUN 2020 - 2022

UTAMI, PUTRI SHOBIROH and Passarella, Rossi and Ubaya, Huda (2024) ANALISIS MODEL CLUSTERING KECELAKAAN LALU LINTAS DI KOTA PALEMBANG MENGGUNAKAN PENDEKATAN MACHINE LEARNING BERDASARKAN DATA SEKUNDER DARI KEPOLISIAN RESOR KOTA BESAR PALEMBANG TAHUN 2020 - 2022. Undergraduate thesis, Sriwijaya University.

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Abstract

Between 20 and 50 million people suffer non-fatal injuries in road accidents every year, while more than a million of these incidents cause death. Road traffic crashes are a significant menace not only to the economy but also to public health. The numbers obtained are objective statistics not subject of personal opinion. This research aims to develop a clustering model using a machine learning approach based on characteristics of incidents and number of victims in traffic accidents in Palembang City, South Sumatra Province, Indonesia. Research will analyse the pattern which observes different relationships among accidents using various clustering techniques such as K-means clustering, Gaussian mixture models (GMM), density-based (DBSCAN), hierarchical clustering, spectral clustering, and OPTICS (ordering points to identify the clustering structure). The result shows that the algorithm called spectral clustering outperforms others with a low Davies-Bouldin score (0.3221), a high Calinski-Harabasz score (14789.9374), and a silhouette coefficient (0.7695). Spectral clustering was found to be the best algorithm out of the six algorithms evaluated for this paper. Keywords: Traffic Accidents, Clustering Model, Machine Learning, Silhouette Coefficient, Davies Bouldin Index, Calinski-Harabasz

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Traffic Accidents, Clustering Model, Machine Learning, Silhouette Coefficient, Davies Bouldin Index, Calinski-Harabasz
Subjects: Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions: 09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User: PUTRI SHOBIROH UTAMI
Date Deposited: 12 Jul 2024 06:06
Last Modified: 12 Jul 2024 06:06
URI: http://repository.unsri.ac.id/id/eprint/150543

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