Developing an NLP-Powered Chatbot Application for MSME Legal Literacy - Syarif Hidayatulloh; Lilyani Asri Utami; Hilda Rachmi (IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia., 2026)
Micro, Small, and Medium Enterprises (MSMEs) play a vital role in the national economy but often face legal challenges due to limited literacy regarding regulations and lack of access to information. This study aims to develop a legal literacy chatbot application for MSMEs based on Natural Language Processing (NLP) using the Rapid Application Development (RAD) method. The development process was carried out iteratively by involving users to ensure the system meets their needs. System evaluation included Black Box testing, usability testing using the System Usability Scale, relevance testing, and performance testing. The Black Box results showed that all functions ran 100% successfully. Usability testing involving 24 respondents obtained an average SUS score of 71.98, which exceeded the standard threshold of 68, indicating that the application is acceptable and easy to use. Relevance testing showed a high level of answer suitability, while performance testing with GTmetrix produced a Performance score of 87%, Structure score of 92%, a fully loaded time of 2.1 seconds, and a total page size of 0.98 MB. These findings highlight that the chatbot application can provide legal information quickly, accurately, and practically, as well as has the potential to improve the legal literacy of MSME actors.