In this research, the face painting recognition of Papua and Papua New Guinea was identified using the Convolutional Neural Network (CNN). This CNN method is one of the deep learning that is very well known and widely used in face recognition. The best training process model is obtained using the CNN architecture, namely ResNet-50, VGG-16, and VGG-19. The results obtained from the training model obtained an accuracy of 80.57% for the ResNet-50 model, 100% for the VGG-16 model, and 99.57% for the VGG-19 model. After the training process, predictions were continued using architectural models with test data. The prediction results obtained show that the accuracy of the ResNet-50 model is 0.70, the VGG-16 model is 0.82, and the VGG-19 model is 0.83. It means that the CNN architectural model that has the best performance in making predictions in identifying the recognition of Papua and Papua New Guinea's face painting is the VGG-19 model because the accuracy value obtained is 0.83.

Twitter is one social media that often provides much information for its users, one of which is information regarding the COVID-19 vaccination. This study aimed to explore and find out what topics are often discussed on Twitter social media. One of which is the topic of COVID-19 vaccination using the Latent Dirichlet Allocation (LDA) method and analysis of the frequency of keywords that often appear with this topic. The Tweet data used in this study was taken from Twitter users worldwide in November 2021. In this study, the results of sentiment analysis were obtained from the tweet data taken, which was divided into positive sentiment and negative sentiment, namely "vaccination" with 40 words and "'Covid19" with 35 words