Authors: Wahyudin; Dwi Fitria Al Husaeni; R. Rasim; Hanhan Maulana; Shah Nazir
DOI: 10.1109/ICIC64337.2024.10956979
Abstract
The Titanic is a British cruise ship that is claimed to be the largest ship ever built in world history. The ship struck an iceberg on its maiden voyage across the Atlantic in 1912 from Southampton to New York. Of the more than 2.200 passengers, almost half died in this tragic accident. This famous incident prompted scientists to research more about the event. This research aims to analyze data and understand the factors that influence passenger survival. Using Machine Learning techniques and a data set consisting of 891 records, researchers tried to determine the relationship between factors such as age, gender, passenger class, and ticket price. This research uses various machine learning algorithms such as Random Forest, Optimize Selection, and Optimize Features to predict the accuracy of each algorithm. These factors may influence passenger survival rates. Specifically, this research aims to compare algorithms based on the percentage accuracy of test data. The research results show that the highest accuracy is achieved by the Random Forest algorithm with weight optimization using Particle Swarm Optimization (PSO). © 2024 IEEE.
Author keywords
Data Mining; Optimize Weighting; Particle Swarm Optimization; Random Forest
Indexed keywords
Engineering controlled terms
Particle swarm optimization (PSO)
Engineering uncontrolled terms
Accurate prediction; Algorithm study; Cruise ships; Large ships; Optimize weighting; Particle swarm; Particle swarm optimization; Random forests; Ship strikes; Swarm optimization
Engineering main heading
Random forests
This article can be accessed at https://www.scopus.com/pages/publications/105004581469
