Designing an Expert System for Evaluating Student Stress Levels: A Novel Instrument Using Backward and Forward Chaining Methods

Abstract

Academic stress is a problem that students often experience, especially when completing final studies such as writing a thesis. This research aims to develop an instrument for measuring students' academic stress levels based on an expert system using forward chaining and backward chaining methods. The research method used is research and development (R&D) with a Borg and Gall design which includes 10 steps. These steps include: (1) Research and information collecting, (2) Planning, (3) Developing a preliminary form of the product, (4) Preliminary field testing, (5) Main product revision, (6) Main field testing, (7) Operational product revision, (8) Operational field testing, (9) Final product revision, and (10) Dissemination and implementation. By following these steps, the research ensures a systematic and thorough development process, leading to a reliable instrument for measuring academic stress. The data collection instrument was the Guttman model academic stress scale (SSA) with 48 valid and reliable items (rxy = 0.785). Data was obtained from 319 IAIN Batusangkar student respondents which were processed descriptively. The results showed that 34.8% of respondents experienced high levels of academic stress, 32.6% moderate, and 32.6% low. Furthermore, this research develops a web-based expert system application to detect students' academic stress levels by using forward chaining, which starts from data to reach a conclusion, and backward chaining, which starts from a goal to verify it with available data. These methods ensure accurate stress level assessments. Through this technological approach, the research provides a comprehensive solution for managing and reducing student academic stress effectively and efficiently, with findings showing that the expert system significantly improves early detection and personalized stress management strategies for students.