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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 and test a genset fuel conversion system from gasoline to HHO gas (brown gas) as a more environmentally friendly alternative. Conventional fossil-fueled generators face challenges in theform of limited resources and the impact of environmental pollution. In this study, HHO gas is produced through a water electrolysis process using an HHO generator that separates water molecules into hydrogen and oxygen using electric current. The test results show that increasing the voltage from 2.58 V to 5.12 V significantly increases the volume of gas produced. At a voltage of 2.58 V, the gas volume reached 110 ml, and increased to 750 ml at a voltage of 4.72 V. The generator set was successfully operated for 1 minute 15 seconds with HHO gas using a separate battery power source. These results demonstrate the potential of HHO gas as an efficient alternative fuel for generator sets. This study recommends further testing with voltage and current variations to find the optimal configuration, as well as the use of a larger power source to increase the efficiency of HHO gas electrolysis.