Open AccessCustomer Critique Analysis System for PT. KCI’s Twitter
Author(s) -
Ahmad Husen,
Sari Widya Sihwi,
Esti Suryani
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1201/1/012006
Subject(s) - usability , computer science , installation , support vector machine , software , analytics , dashboard , sentence , software engineering , world wide web , operating system , artificial intelligence , database
Commuter Line is one of the main choices for users of public transport in Jakarta. Commuter Line in Indonesia is managed by PT. Kereta Commuter Indonesia (PT. KCI). PT. KCI has an official Twitter account @CommuterLine. The purpose of this research was built Customer Critique Analysis System for Twitter PT. Kereta Commuter Indonesia using Support Vector Machine (SVM). The software engineering method used in this research is Component-Based Software Engineering (CBSE). Applications built in this research uses some components/libraries, which are Tweetsharp, LibSVM, Metronic, Kendo UI and JQCloud. The results of this research is a useful analytics application to perform grabbing and tweet data analysis from Twitter account @CommuterLine, and a dashboard to display the results of the analysis in graphical form. The test results show that the system meets the functional and nonfunctional requirements from the user. Testing is done by installing the application on the server PT. KCI, then it was tested by user.. Non-functional testing was done by measuring application performance and usability. Performance measured is classification accuracy and running time of the program. Accuracy performance testing resulted in average sentence classification accuracy of 80.4%, and the accuracy of complaint classification type of 82.3%. The average running time is 3 minutes 25 seconds.