ANALISIS DATA PENYEBAB KECELAKAAN PESAWAT KOMERSIL DI DUNIA MENGGUNAKAN DATA BAAA DENGAN PENDEKATAN METODE K-MEANS CLUSTERING

IQBAL, M. DION and Passarella, Rossi (2022) ANALISIS DATA PENYEBAB KECELAKAAN PESAWAT KOMERSIL DI DUNIA MENGGUNAKAN DATA BAAA DENGAN PENDEKATAN METODE K-MEANS CLUSTERING. Undergraduate thesis, Sriwijaya University.

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Abstract

This study focuses on analysing data on the causes of commercial aircraft accidents in the world using data from the Bureau of Aircraft Accident Archives from 1918-2021. Using K-means clustering to group the causes of aircraft accidents and using the silhouette index to determine the best number of clusters to use in K-means clustering. The purpose of this study is to find data from the correlation between the causes of airplane accidents and the number, then the results of these findings will determine the severity of the accident, and determine the cause of each severity level. The results of this study are that there are 2 accident clusters, other findings in the second cluster are clusters based on the range of the number of victims in each cluster. The second cluster is dominated by the severe category with technical factors as a frequent cause.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Data science, Computer Science
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:	Mr. M Dion Iqbal
Date Deposited:	23 Nov 2022 07:29
Last Modified:	23 Nov 2022 07:29
URI:	http://repository.unsri.ac.id/id/eprint/82582

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