Comparative Analysis of Classification Methods in Sentiment Analysis: The Impact of Feature Selection and Ensemble Techniques Optimization - Defit, Sarjon; Windarto, Agus Perdana; Alkhairi, Putrama (Universitas Amikom Purwokerto, 2024)
Optimizing classification methods (forward selection, backward elimination, and optimized selection) and ensemble techniques (AdaBoost and Bagging) are essential for accurate sentiment analysis, particularly in political contexts on social media. This research compares advanced classification models with standard ones (Decision Tree, Random Tree, Naive Bayes, Random Forest, K-NN, Neural Network, and Generalized Linear Model), analyzing 1,200 tweets from December 10-11, 2023, focusing on