Building automatic customer complaints filtering application based on Twitter in Bahasa Indonesia

Abstract

Twitter has become a media to provide communication between a company with its customers. The average number of Twitter active users monthly is 330 million. A lot of companies realize the potential of Twitter to establish good relationship with their customers. Therefore, they usually have one official Twitter account to act as customer care division. In Indonesia, one of the company that utilizes the potential of Twitter to reach their customers is PT Telkom. PT Telkom has an official customer service account (called @TelkomCare) to receive customers’ problem. However, because of this account is open for public, Twitter users might post all kind of messages (not only complaints) to Telkom Care account. This leads to a problem that the Telkom Care account contains not only the customer complaints but also compliment and ordinary message. Furthermore, the complaints should be distributed to relevant division such as “Indihome”, “Telkomsel”, “UseeTV”, and “Telepon” based on the content of the message. This research built the application that automatically filter twitter post messages into several pre-defined categories (based on existing divisions) using Naïve Bayes algorithm. This research is done by collecting Twitter message, data cleaning, data pre-processing, training and testing data, and evaluate the classification result. This research yields 97% accuracy to classify Twitter message into the categories mentioned earlier.