Chatbot Adoption based on Lean Management: A Case Study of Interrogation Tasks in Betong Police Station

Authors

  • Keitpansak Bilabdulla Management of Information Technology, Faculty of Engineering, Prince of Songkla University, Kho Hong, Hatyai, Songkhla 90110, Thailand.
  • Numtip Trakulmaykee Information and Communication Technology, Faculty of Science, Prince of Songkla University, Kho Hong, Hatyai, Songkhla 90110, Thailand.

Keywords:

chatbot, dialogflow, police station, lean, information

Abstract

The Interrogation Department of Betong Police Station had service problems on Facebook Messenger. People had to wait a long time because of the insufficient manpower for 24 service hours and in the police lack of expert staff in every case consulting. Therefore, this research adopted the chatbot in Interrogation Tasks of Betong Police Station. The research objective was to: (1) design and develop the chatbot for supporting citizen laws service of Investigation Department in the police station, and (2) evaluate the efficiency based on Lean concept and assess user satisfaction with the chatbot. This chatbot was developed based on Lean concepts and plugged in with Facebook Messenger. The results showed that the new process or post Lean can reduce wasted time around 1.507.98 minutes (99.80%), and the percentage of efficiency was 100, increasing around 99.21 percent. In addition, the results indicated that the level of user satisfaction was high (4.09), and the system can interact quickly (4.19). These results indicated that users are satisfied with the chatbot adoption in Interrogation Department of Betong Police Station because the chatbot can reduce their waiting service time.

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Published

2023-12-26

How to Cite

Bilabdulla, K., & Trakulmaykee, N. (2023). Chatbot Adoption based on Lean Management: A Case Study of Interrogation Tasks in Betong Police Station. Recent Science and Technology, 15(3), 687–701. Retrieved from https://li01.tci-thaijo.org/index.php/rmutsvrj/article/view/253368

Issue

Vol. 15 No. 3 (2023): September - December 2023

Section

Research Article

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