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One of the museums found in Bali is Subak museum in Tabanan Regency. The establishment of this Museum aims to preserve the traditional institution called Subak as a noble national cultural heritage, and to introduce to the younger generation and foreign tourists about the unique traditional irrigation system in Bali. Lack of supporting facilities in delivering information, making tourists who visit Subak Museum have minimal information. The solution needed in Subak museum is an Android-based E-Tourism application that is supported by Qr-Code technology so as to provide an interesting presentation of data. In making this application using the development of the Waterfall method and designed using the Unified Modeling Language (UML) with the Java programming language for Android and PHP for web services, and MySQL as a database. So that produced an android-based system in Subak museum Tabanan Regency. Based on the results of the tests carried out it can be concluded that the black box testing system functions have been running according to the planning. Then the result of the testing of users using questionnaires generated Application Benefits scores 90.8%, Ease of 86.93%, Interface 82% and Content 90.2%. 

This study aims to analyze the sentiment of iPhone product reviews fromAmazon using the BERT (Bidirectional Encoder Representations from Transformers) model to classify reviews as either positive or negative. The dataset, sourced from Kaggle, includes text reviews and star ratings, where high ratings indicate positive sentiment and low ratings indicate negative sentiment. After text preprocessing steps, including data cleaning, tokenization, and sentiment labeling, the BERT model was fine-tuned for sentiment classification, with the data split into training, validation, and test sets. Evaluation results demonstrate that the BERT model achieves a high classification accuracy, with an accuracy rate of 93.9% and a balanced F1 score between precision and recall. Confusion matrix evaluation also indicates that the model consistently identifies both positive and negative sentiments. This study shows that Transformer-based models like BERT are highly effective in understanding customer opinions in e-commerce, with broad application potential for data-driven decision-making in marketing strategies and product development.

This research aims to design a website-based online store by utilizing a recommendation system with content-based filtering. The recommendation system is useful to help buyers get product suggestions that are in accordance with their preferences. The development method used in this research is the Waterfall model with the stages of needs analysis, design, program code generation, and testing. Researchers also use the UML model to help design the system and use the Laravel framework for website development. Based on the results of this study, the online store system designed has benefits for customers, because they can shop anywhere without having to come to the store directly. The recommendation system used also helps customers in choosing perfumes that match their preferences.