Browsing by Author "Sari, Intan Permata"

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    ANALISIS SENTIMEN TERHADAP LAYANAN GOFOOD PADA MASA AWAL DAN PENURUNAN PANDEMI MENGGUNAKAN METODE NAÏVE BAYES
    (Elfitra, 2022-07) Sari, Intan Permata; Risanto, Joko
    Coronavirus is a group of viruses that can infect both animals and humans. Coronavirus usually causes respiratory tract infections in humans, ranging from coughs, colds to Middle East Syndrome (MERS), and Severe Acute Respiratory Syndrome (SARS). Many studies have been conducted to determine sentiment, especially regarding the effect of delivery services during the COVID-19 period. This study aims to compare the presentation of public sentiment regarding GoFood services in the early days of the pandemic and the decline of COVID-19 and to determine the level of accuracy in conducting sentiment analysis. This study used the Naïve Bayes method which is useful for classifying data and used a Confusion Matrix to see how well the accuracy level of the classification results is. In the process of data classification is divided into two, positive and negative. The final result of this research is that at the beginning of the pandemic, the sentiment was in the form of a positive sentiment was 52% and a negative value was 48%. Then during the pandemic decline, positive sentiment was 74% and a negative value was 26%. Based on this process, the accuracy rate at the beginning of the pandemic was 82.67% and during the decline in the pandemic, the accuracy level was 70.58%. So analyzing sentiment data using the Naïve Bayes method achieved satisfactory results.