Enhancing Problem-Solving Reliability with Expert Systems and Krulik-Rudnick Indicators

Enhancing Problem-Solving Reliability with Expert Systems and Krulik-Rudnick Indicators

problem-solving;krulik and rudnickmethod; forward chaining;certainty factor; confusion matrix

Problem-solving is one of the skills needed in the 21st century, but there is a significant gap between the ideal conditions and the reality of students' problem-solving skills. One method that can improve students' problem-solving skills is Krulik and Rudnick, but implementing this method with an expert system to improve problem-solving skills is still limited. This research aims to build an expert system to determine the level of problem-solving using Krulik and Rudnick's problem-solving indicators processed using the forward chaining and certainty factor algorithms. The study had five stages: data analysis, rule generation, certainty measurement, prediction, and testing. The data was processed by developing 5 Krulik and Rudnick problem-solving indicators into 35 statements. Each statement was categorized using Forward Chaining by producing three rules: low, medium, and high. The problem-solving level obtained is calculated using the Certainty Factor for a confidence value. The system's prediction results were evaluated using a confusion matrix, resulting in an accuracy of 80%, a precision of 92%, and a recallof 85%, indicating the system's reliable performance in measuring the level of problem-solving. This research can be used as a reference to support problem-solving in various more advanced educational and professional environments.

Lita Sari Muchlis1*, Jufriadif Na’am2, Addini Yusmar3, Khairiyah Khadijah4, Sri Wahyuni5, Naufal Ibnu Salam6

https://jurnal.iaii.or.id/index.php/RESTI/article/view/6333/1046

Universitas Islam Negeri Mahmud Yunus, Batusangkar, Indonesia

17-04-2025

FAJAR BAGUS W

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