The Role of Natural Language Processing in Enhancing Chatbot Effectiveness for E-Government Services - Mungkap Mangapul Siahaan; Richard Andre Sunarjo; Rizky Sebastian; Syahrul Muarif Wahid (CORISINTA, 2025)
The rapid digital transformation of public administration has led to the adoption of (B) Natural Language Processing (NLP)-powered chatbots to enhance the accessibility, efficiency, and responsiveness of (O) e-government services. However, despite their increasing deployment, many government chatbots still struggle with intent recognition, response accuracy, multilingual processing, and user engagement, limiting their effectiveness. This study investigates (M) the role of NLP in improving chatbot performance within e-government services by evaluating four case studies: Ask Jamie (Singapore), UK Government Digital Assistant, MyGov Corona Helpdesk (India), and Gov.sg Chatbot. Using a mixed-methods approach, this research assesses chatbot effectiveness based on accuracy, response time, query resolution rate, and user satisfaction metrics. The findings indicate that (R) NLP-driven chatbots significantly outperform rule-based systems, with higher accuracy (up to 89%), faster response times (~2.1 seconds), and improved query resolution rates (92%), demonstrating their capacity to automate public service delivery efficiently. However, key challenges remain, including bias in NLP models, data privacy concerns, and the difficulty of integrating NLP chatbots into legacy IT infrastructures. Additionally, multilingual processing remains a limitation, affecting inclusivity for diverse populations. To overcome these challenges, this study proposes advancements in adaptive NLP models, real-time learning algorithms, ethical AI frameworks, and blockchain-based security solutions to ensure fair, secure, and transparent chatbot interactions in digital governance. These findings contribute to the growing body of research on AI-driven public service automation and highlight the potential of NLP to enhance (C) citizen-government interactions, reduce administrative burdens, and improve trust in e-government platforms. Future research should focus on bias mitigation, improving multilingual NLP capabilities, and integrating AI ethics into chatbot governance frameworks to ensure sustainable, scalable, and citizen-centric e-government chatbot solutions.