The Concept of Big Data in Bureaucratic Service Using Sentiment Analysis

Author:

Muliawaty Lia1,Alamsyah Kamal1,Salamah Ummu1,Maylawati Dian Sa'adillah2

Affiliation:

1. Universitas Pasundan, Bandung, Indonesia

2. UIN Sunan Gunung Djati Bandung, Bandung, Indonesia & Universiti Teknikal Malaysia Melaka, Melaka, Malaysia

Abstract

The implementation of bureaucratic reform in Indonesia is not optimal and faces various obstacles. At present, public services demand excellent service and meet public satisfaction. The obstacles are rigid bureaucracy, incompetent bureaucrats or apparatuses, not professional, and there are technological gaps. Rapid technological development, such as digital technology and big data, has not been responded to positively by most bureaucrats. Big Data has a great potential for improving bureaucratic and public services. With a qualitative method and a waterfall software development life cycle, this article provides the design of a bureaucracy sentiment analysis application which implements Big Data technology for analyzing the opinions about bureaucratic service in Indonesia. This is for the purpose that the bureaucratic services can be improved based on societal opinion. The results of the experiment using RapidMiner showed that sentiment analysis as a Big Data technique for bureaucratic service based on societal opinion can be used to evaluate performance better.

Publisher

IGI Global

Reference52 articles.

1. Deep Learning Methods and Applications

2. Arockia, P. S., Varnekha, S. S., & Veneshia, K. A. (2017). The 17 V’s of Big Data. International Research Journal of Engineering and Technology, 4(9), 3–6. Retrieved from https://irjet.net/archives/V4/i9/IRJET-V4I957.pdf

3. Aylien. (n.d.). Aylien Text Analytics. Retrieved from https://aylien.com/

4. BoochG. (1998). Object-Oriented Analysis and Design (2nd ed.). Santa Clara, CA: Addison-Wesley.

5. Booch. (2005). The Unified Modeling Language User Guide. Addison-Wesley. Retrieved from http://books.google.com/books?id=xfQ8JCbxDK8C&pgis=1

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