Analisis Sentimen Terhadap Penutupan Tiktok Shop Dengan Metode Naive Bayes

Riyan Fahmi Gunawan; Nurirwan Saputra; Ari Kusuma Wardana; Ahmad Riyadi

doi:10.59581/jusiik-widyakarya.v2i3.3948

Authors

Riyan Fahmi Gunawan Universitas PGRI Yogyakarta
Nurirwan Saputra Universitas PGRI Yogyakarta
Ari Kusuma Wardana Universitas PGRI Yogyakarta
Ahmad Riyadi Universitas PGRI Yogyakarta

DOI:

https://doi.org/10.59581/jusiik-widyakarya.v2i3.3948

Keywords:

Sentiment Analysis, Tiktok Shop, Preprocessing, Naive Bayes, Streamlit

Abstract

Nowadays, advances in information and communication technology have had a major impact on various sectors of life, including in the field of trade and e-commerce. However, as it happens in the scope of social media, TikTok Shop is also dealing with challenges and changes. One of the issues that is sticking out and is currently hot is the permanent closure of the TikTok Shop feature that has occurred in Indonesia. This research will carry out several processes starting with data collection, then data labeling, data preprocessing, data sharing, weighting training data, using the Naive Bayes method, and ending with testing. In this study, the results of the implementation that has been made or built are discussed. The method used is the Naive Bayes Classifier Method to classify training data as much as 800 data, which is 80% of the total data. Then, testing is carried out using 200 testing data, which is 20% of the total data. The evaluation results show an accuracy value of 73%. In addition to the accuracy value, this research also recorded the precision, recall, and F1 score values. The classification that appears most often and contributes the highest in these values is the Positive classification as much as 420 data or 42% of the total data used..

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