Abstract

The rise of Social Media gets all the conveniences in communicating like in real life. The activities that users of social media can engage in also vary, ranging from searching for information about products, comparing them with other products to making online purchases. Online stores are widely used by consumers because they are easy and fast in the transaction process, including the TikTok application which has a new feature, TikTok Shop released last year on April 17, 2021. This application is widely used among teenagers. Sentiment analysis is a technique that can extract text data to obtain information about positive or negative sentiments. This study aims to create an application that can classify sentiments into positive or negative sentiments to determine how interested Indonesian people are in using the TikTok application when doing business or when interacting and dealing with slang in TikTok Shop sentiment analysis. The opinion data of TikTok stores in this study was taken from responses on Twitter. This research was conducted using the Naïve Bayes Classifier (NBC) method. The number of tweets examined in this study was 1230 tweets. With the number of negative words as many as 567 data and positive as many as 663 data. Testing is performed by implementing the Python programming language. The results of classification using Naïve Bayes Classifier algorithm found an accuracy value of 74.32%.

Keywords

Social Media, Online shop, TikTok Shop , TikTok, Naïve Bayes Classifier, slang word.

Biographies

Asmia Nur Khaliza is a final year undergraduate student in the department of informatics, Jenderal Achmad Yani University, Cimahi, Indonesia. Her primary interests are systems analysis, data and software engineering.

Yulison Herry Chrisnanto is an Associate Lecturer. Received her Master’s degree in Informatics from Insitute Techonology Of Bandung. Amongst her Researcher interest are Data mining and Software Engineering.

Puspita Nurul Sabrina is an Associate Lecturer. Received her Master’s degree in Informatics from Insitute Techonology Of Bandung. Amongst her Researcher interest are Data mining, Software Quality, Business Intelegent.

Asep Id Hadiana received his Master’s degree in Enterprise Information System from Indonesian Computer Univerity and a Doctor of Philosophy from Technical University of Malaysia Melaka. He is a lecturer in the Informatics Department, Faculty of Science and Informatics, Universitas Jenderal Achmad Yani. Amongst his research interest are Cyber Security, Data Mining, Spatial Analysis, Location Based Services and Geographic Information Systems.

Asmia Nur Khaliza

Affiliation

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Sentiment Analysis Online Shop Social Media On Tik-Tok App With Naive Bayes Classifier (NBC) Method