ANALYSIS AND DESIGN OF A SURVIVAL PREDICTION SYSTEM USING THE SUPPORT VECTOR MACHINE (SVM) ALGORITHM AND TITANIC DATASET

Abstract

A century has passed since the sinking of Titanic on April 15, 2022. The disaster has sparked speculation and public and scientific interest in the shipwreck. This study aims to determine the survival rate of Titanic passengers using the Support Vector Machine algorithm. SVM is used as the model by dividing the dataset into 80% training data and 20% testing data, and then calculating the model's accuracy rate using the Holdout method, which produces 81.12%, and K-Fold Cross Validation, which produces an average score of 81.03%. The result of this study is a simple survival prediction system for ship passengers. Keywords : Titanic, Support Vector Machine, Hold Out Method, K-Fold Cross Validation, Survival Prediction