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Currently, climate change due to global warming is a concern for many parties. The greenhouse gas emissions level is increasing day by day. The major contributors to Air pollution are the greenhouse effect. Transportation accounts for about 27% of air pollution, and governments in various countries use electric vehicles to reduce air pollution. However, the success of using electric vehicles is depending on perception, people's sentiment, and understanding. The main purpose of this research is to find out how public sentiment towards electric vehicles is through tweets and comments on the Twitter social media platform using sentiment analysis. The data obtained are 1084 tweets and comments. The data were classified using the Naïve Bayes method, K-Nearest Neighbor, and Decision Tree. The results showed that the Naïve Bayes Classification Method gave better results than K-Nearest Neighbor, and Decision Tree with an accuracy rate of 94% positive sentiment by 53%, negative sentiment by 38%, and neutral sentiment by 9%. So, it can be concluded that public sentiment towards electric vehicles is quite good based on conversations on the Twitter social media platform. In addition, the author also visualizes the results of the analysis in the form of graphs and word clouds so that they can help the electric vehicle industry players to understand public sentiment better and more accurately.

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Series Arc Fault is one of the disturbances of arcing jump is caused by gas ionization between two ends of damaged conductors or broken wire forming a gap in the insulator. Series arc fault is the primary driver of electrical fire. However, lack of knowledge of the disturbance of series arc fault causes the problem of electrical fire not be mitigated. Magnitude current is not capable to detect of series arc fault. Therefore, this paper proposes fast fourier transform (FFT) to detect series AC arc fault in low voltage using microcontroller ARM STM32F7NGH in real time. A cheap and high speed of microcontroller ARM STM32F7NGH can be used for FFT computation to transform signal in time domain to frequency domain. Moreover, in this paper, protection of series AC arc fault is proposed in the real time mode. In this experimental process, some various experiments are tested to evaluate the reliability of FFT and protection with various load starts from 1 A, 2 A, 3 A, 4 A in resistive load. The result of this experiment shows that series AC arc fault protection with STM32F7 microcontroller and FFT algorithm can be utilized to ensure series AC arc fault properly.