The relocation state capital of Indonesia raises various responses, especially from the Indonesian people.  The discussion related to these issues is very interesting to study, how are the positive and negative sentiments of the Indonesian towards the government's decision. This study aims to analyze the sentiments of the Indonesian people regarding the relocation state capital of Indonesia, including the chosen name of Nusantara on Twitter. In this study, a comparison of 3 algorithms is used, namely the Support Vector Machine (SVM), Naïve Bayes, and K-Nearest Neighbor (KNN) algorithms. From this study, the results obtained are 1,141 positive comments, while negative sentiments are 591 comments. This shows that the Indonesian people have a positive opinion towards the new capital city of Indonesia. In the classification and model testing phase, 10-fold cross validation is used. From these tests, the SVM algorithm obtained an accuracy value of 85.71%, the Naïve Bayes algorithm obtained an accuracy value of 76.70%, the KNN algorithm obtained an accuracy value of 52.74%. This study shows that the SVM algorithm can work better than the Naïve Bayes algorithm and KNN. The accuracy value for the KNN algorithm obtains a low value, this is because the KNN algorithm is sensitive to features that are less relevant.

The best application predicate has been awarded to the application that has the highest downloads and high star rating on Google Play Store. In rating an application, user comments need to be considered because many stock investment apps have almost the same downloads and star ratings, so the title of best app is a problem. Based on this condition, this research aims to analyze user feedback of stock investment applications as a variable to determine which stock investment application is the best on the Google Play Store. This study using the Support Vector Machine (SVM) classification method with the support of Rapid Miner to carry out the calculation process. From this research, it produces positive sentiment values for each application, namely HSB Investment about 1,134 positive sentiments with an accuracy value of 88.70%, Ajaib about 936 positive sentiments with an accuracy value of 61.89%, Pluang about 703 positive sentiments with an accuracy value of 68.25%, Bibit about 322 positive sentiments with an accuracy value of 64.89%, and Stockbit about 124 positive sentiments with an accuracy value of 66.95%. So it can be concluded that the HSB application as the best stock investment application based on user comments reviews where this application has the most positive sentiment reviews with a high accuracy value.