Design and Development of a WhatsApp Chatbot-Based Expert System Using the Depth-First Search Algorithm for Thesis Topic Recommendation

Abstrak

The rapid development of digital technology has encouraged the creation of various intelligent systems that can support decision-making processes, one of which is an expert system. In the academic environment, students often encounter difficulties in determining appropriate thesis topics that align with their areas of interest. Therefore, this study aims to develop an expert system integrated with a WhatsApp chatbot to assist students in identifying suitable thesis themes based on their academic interests. The system employs the Depth-First Search (DFS) algorithm as a problem-solving approach due to its flexibility in exploring decision paths within the knowledge base. The expert system is implemented through a WhatsApp chatbot interface to ensure ease of use, as the messaging interface is already widely familiar among university students. This approach allows users to interact with the system naturally without the need to learn a new interface. The results of system testing indicate that the developed expert system effectively assists students in determining thesis topics. Evaluation results show an accuracy level of 95.4%, demonstrating that the proposed system provides reliable recommendations. Furthermore, the use of a chatbot-based interface enhances user accessibility and usability. In conclusion, the integration of an expert system with the DFS algorithm and a WhatsApp chatbot interface provides an effective and user-friendly solution for supporting students in selecting appropriate thesis topics based on their interests.