Internet Influence Being able to influence people through the internet. We can get information. Besides that, we can also give positive and negative opinions for specific reviews. Reviews or commonly called reviews are an essential factor in knowing the quality of a smartphone product. This factor can be used to assess or provide opinions in text reviews that follow the quality of a smartphone given in society. Smartphones began to develop with various smartphone models to use Twitter social media such as Samsung and Vivo. These two Smartphone Brands, not a few Indonesian people express their opinions regarding these products from Price, Memory, and Camera. The main purpose in this final assignment is to evaluate the effect on smartphones using a review-based sentiment analysis method from each tweet that customers have attached with the KNN algorithm. In the application of sentiment analysis requires an algorithm that can perform a classification of public opinion or sentiment. In this case, previous research can be used as a reference in terms of algorithms, sentiment analysis, and classification. The KNN (K-Nearest Neighbor) algorithm is a supervised learning algorithm where the results of the new instance are classified based on the majority of the k-nearest neighbor category. In the final project, sentiment analysis of Samsung and Vivo smartphone products. Using an open-source website application, namely Jupyter Notebook, using the language programming, namely, python, which starts with the process of coding data and collecting data through web-scraping using tweepy because it retrieves data via APIKey, which has been requested directly from Twitter on May 5, 2021, until July 26, 2021, with the accuracy results obtained, obtaining the highest accuracy of 94.33 % for Samsung data and 96.79% for Vivo data.
Keywords: Sentiment Analysis, APIKey, Classification, KNN, K-Nearest Neighbor, Samsung, Vivo