Analisis Sentimen Tweet Terhadap Penggunaan Layanan JNE & JNT Menggunakan Metode Naive Bayes
Keywords:
Shipping Expedition, Nave Bayes, Python, ScrapingAbstract
Delivery service is something that is close to the community, delivery services are still used by the community because it is considered very important to send goods over long or close distances. Because as we all know, as we all know, that in the context of accelerating the handling of Covid-19 (Corona Virus Disease 2019), the government issued PP No. 21 of 2020 concerning PSBB (Large-Scale Social Restrictions). With the enactment of PSBB, it brings a new culture of digitization in many sectors, including the social public sector. So that most people's shopping activities are forced to switch to using an online system and make delivery services very functional at this time. Therefore, the researcher intends to conduct this research which is intended to determine customer satisfaction with JNE and JNT shipping expeditions. The research was conducted by taking tweet sentiment using Python, and then analyzing the respondents' sentiment using the Naïve Bayes method. A total of 955 data were obtained, then the researchers took as many as 243 for retesting, data collection was carried out on January 31, 2022 to February 16, 2022. The results of the classification of positive, negative and neutral sentiment tweets from existing sentences for each delivery service have been obtained that JNE got 0 positive responses, 18 negative responses and 56 neutral responses. Meanwhile, JNT received 0 positive responses, 2 neutral responses and 167 negative responses. From this it can be explained that there are still many users of JNE and JNT shipping expedition services that have not received good service. The results of the test using the Nave Bayes method with the Gaussian Density formula on continuous data resulted in an accuracy of 58.02%, precision 43.33%, recall 41.67%.
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