Sentiment Analysis Of Public Enthusiasm Towards Electric Motorcycles Using The Naïve Bayes Algorithm - Sri Ratna Dewi; Rakhmat Kurniawan R (International Journal of Science and Environment (IJSE), 2025)
Electric motorcycles have emerged as an alternative to reduce dependence on fossil fuels and support environmentally friendly transportation. In Indonesia, the local brand Polytron has introduced several electric motorcycle products at affordable prices. However, public responses remain varied, influenced by price, infrastructure, and awareness. This study aims to analyze public enthusiasm for Polytron electric motorcycles using the Naïve Bayes Classifier (NBC), which has been proven effective in text classification [1]. A dataset of 1000 comments was collected from social media platform X through web crawling. The preprocessing included case folding, cleaning, tokenizing, normalization, stopword removal, and stemming[2]. Sentiment labeling was conducted using the InSetLexicon, and TF-IDF weighting was applied before classification in Python using Google Colab [3]. The results indicated that most public opinions expressed positive sentiment, highlighting benefits such as cost savings and environmental friendliness [4]. Negative sentiments focused on limited charging infrastructure and higher purchase prices. The Naïve Bayes model achieved reliable performance, confirming its suitability for Indonesian sentiment analysis tasks [5]. This study contributes to understanding public perception of local electric vehicles and provides useful insights for policymakers and manufacturers in promoting sustainable transportation.