Sentiment Analysis on Import Tariff Policy and Gold Price Increase with TF-IDF - siti masripah; Rizal Amegia Saputra (Jurnal Riset Informatika, 2025)
Changes in global economic policy, such as Donald Trump's import tariff policy in 2025, have generated various public responses recorded through social media such as Twitter. Analysis of this public opinion is important to understand public perception of the dynamics of gold prices as a strategic commodity. This study aims to analyze public sentiment towards the issue of tariff policies and gold using TF-IDF feature extraction. To overcome class imbalance in tweet data, the Synthetic Minority Over-sampling Technique (SMOTE) technique was used. The dataset was obtained from Twitter with the keywords "trump", "tariffs", and "gold", then preprocessing and sentiment labeling (positive, negative, neutral) were carried out. The results of the analysis showed that 88.8% of tweets contained positive sentiment, 6.9% negative, and 4.1% neutral. The model evaluation produced an accuracy of 81.23%, with the highest precision in the positive class (0.81) and a recall of 1.00. These findings indicate that the issue of tariff policies is associated optimistically by the public because it is considered beneficial to gold prices.