Bilingual Feedback Management System for Frontline Services with Sentiment Analysis using Naïve-Bayes Algorithm


Authors
  • Benjie R. Samonte
  • Batangas State University ARASOF-Nasugbu
Published in


Abstract
  • The purpose of this research is to develop a feedback management system that uses a modern approach of technologies to aid the existing feedback management system used in the university. The study employed Sentiment Analysis using Naïve-Bayes Algorithm which was used in determining the polarity of the customers' feedbacks or suggestions. In order to come up with an effective and reliable system, the researcher adopted the incremental software development model as software methodology, wherein it delivers a series of releases, called increments. It progressively provides more functionality for the customer as each increment is delivered. One hundred eight (108) customers including seven office heads and one quality management staff were chosen as the respondents of the study. Based on the findings, the developed feedback management system (mobile and web applications) was effective in terms of its overall ease of use, portability and functionality for it received a respectable rating from all respondents. It also showed that the system has passed the overall criteria of its technical quality as well as it eliminates the identified common problems encountered using the existing system. Likewise, the system provides performance reports of each office to determine which among the offices are performing well based on feedbacks. Significantly, this innovation will be an effective feedback mechanism tool in the University to address the concerns of the customers and other stakeholders and provide possible merits and rewards to performing offices.


Keywords
  • Feedback Management System, Sentiment Analysis, Naïve-Bayes Algorithm, Feedbacks




Cite As
  • APA 7th Edition:
    Samonte, B. (2019). Bilingual Feedback Management System for Frontline Services with Sentiment Analysis using Naïve-Bayes Algorithm. Innovatus, 2(1), 83-88.
  • Harvard:
    Samonte, B., 2019. Bilingual Feedback Management System for Frontline Services with Sentiment Analysis using Naïve-Bayes Algorithm. Innovatus, 2(1), pp.83-88.
  • IEEE:
    [1] B. Samonte, "Bilingual Feedback Management System for Frontline Services with Sentiment Analysis using Naïve-Bayes Algorithm", Innovatus, vol. 2, no. 1, pp. 83-88, 2019.


References
  • J. Rousel, "Why Suggestion Boxes Fail," 2014. [Online]. Available: https://blog.kainexus.com/improvement-disciplines/suggestion-box/why-they-fail.
  • K. Roebuck, Sentiment Analysis: High Impact Strategies - What You Need to Know: Definitions, Adoptions, Impact, Benefits, Maturity, Vendors, Emereo Publishing, 2016.
  • F. F. Patacsil, " Blog Comments Sentence Level Sentiment Analysis for Estimating Filipino ISP Customer Satisfaction," in International Conference on Data Mining, Civil and Mechanical Engineering, Bali, Indonesia, 2015.
  • F. F. B. a. B. E. V. Comendador, "Adoption of Opinion Mining in the Faculty Performance Evaluation System by the Students Using Naive-Bayes Algorithm," International Journal of Computer Theory and Engineering, vol. 18, 2016.
  • M. M. Pinpin, "Classification of Emotions Expressed by Filipinos through Tweets," International Association of Engineers, 2015.
  • A. R. M. a. P. L. F. Frederick F. Patacsil, "Estimating Filipino ISPs Customer Satisfaction Using Sentiment Analysis," Research Gate, 2015.
  • I. Sommerville, Sofware Engineering 9th Edition, Addison-Wesley, 2011.


Cited By
  • No citations found yet