Paper Title
Courier Service Evaluation using Text Mining: A Case Study in PT. Pos Indonesia

Customer reviews are an essential reference to measure product performance in many aspects. Social media is suitable as a customer review data source because it has a large number of online volunteers who write their reviews. To analyze online customer review, artificial intelligence is needed. Many studies have applied the artificial intelligence approach, but a few studies focus on the courier service industry in Indonesia. The courier service industry has proliferated in the last few years. Thus, the companies in this industry need to reach a broader market and understand their customers’ preferences promptly. Therefore, in this research, text mining and sentiment analysis methods were applied to analyze the customers’ preference. The sentiment analysis approach used in this research is the supervised machine learning and Support Vector Machine (SVM) algorithm. Four hundred fifty customer reviews were collected from Twitter in Bahasa Indonesia for three products of PT. Pos Indonesia. Keywords - SVM, Text Mining, Sentiment Analysis, Courier Service