Analisis Sentimen Survei Regsosek pada Twitter Menggunakan Algoritma K-Nearest Neighbor (K-NN)
Keywords:
K-Nearest Neighbor, Regsosek, Sentimen analysis, TwitterAbstract
Indonesia in 2022, will experience a shift in adaptation to recovery from the pandemic as well as rising global commodity prices due to the impact of the Ukraine-Russia war. The government in its efforts to deal with this situation, one of which is by transforming data into one data through the 2022 Social Economic Registration (Regsosek) as a requirement for social protection system reform. However, in practice, Research and Research has become quite a public concern, where the content is almost the same as previous surveys conducted by BPS, which raises questions about the effectiveness of this survey. This study aims to determine the sentiments of each opinion on social media Twitter regarding 2022 Social Security. This research implements the K-Nearest Neighbor (K-NN) method to analyze sentiment in tweets. Data obtained from Twitter by scrapping. The polarity percentage results from the tweets obtained are dominated by negative opinions. The best application of the K-Nearest Neighbor (K-NN) algorithm is using the parameter k = 3. The model built shows very good performance with an accuracy of 96%, a recall of 100%, and a precision of 0,96%.
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