Adam Ghazy Al Falah

Digitalization is an important step in improving the efficiency of public services, particularly in managing queues in government institutions such as sub-district offices. Kelurahan Gebang Putih Surabaya faces significant challenges in managing its manual queue system, which often results in discomfort for the public due to long waiting times, exceeding 5 minutes. This reduces public satisfaction and causes inefficiencies in the queue process. To address this issue, this study aims to develop and implement a digital queue system that can be accessed both online and on-site, using the User-Centered Design (UCD) approach. This approach ensures that every aspect of the system's design and development focuses on user needs through an iterative process, where the design is adjusted based on direct feedback from users. The proposed solution in this study includes the creation of a mobile and website-based queue system, allowing the public to easily take a queue number online and also enabling quick on-site queueing with a wait time of less than 10 seconds. Another advantage of this system is its automated reporting feature, which facilitates documentation and queue reports, thereby accelerating administration and monitoring to the city government. The results show that the implementation of this system significantly reduces the queue-taking time from over 5 minutes to less than 10 seconds, successfully transforming the manual system into a more efficient digital system, and streamlining the reporting process to the government, which in turn improves the quality and satisfaction of public services.

Residents of Gebang Putih, Surabaya, often face challenges in accessing administrative information, such as procedures for creating ID cards, updating family data, and registering for marriage. To address these issues, a chatbot based on Dialogflow was developed and integrated with the Telegram platform and a mobile application called Kagapi. This study included data collection from official government websites, interviews with local office staff, and dataset preparation for chatbot training. The results showed that the chatbot achieved a 92% accuracy rate in understanding and responding to user queries, with an average response time of 2-3 seconds. Integration with the mobile application expanded service features, including online queue management. Testing and evaluation by local office staff and residents indicated that the chatbot improved information accessibility and service efficiency by up to 80%. This chatbot demonstrates the potential to serve as an innovative solution in enhancing public service transparency and accessibility.