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

Lita Sari; Jufriadif Ma'am; Addini Yusmar; Khairiyah Khadijah; Sri Wahyuni; Naufal Ibnu Salam

doi:10.29207/resti.v9i2.6333

Lita Sari UIN Mahmud Yunus Batusangkar
Jufriadif Ma'am Universitas Nusa Mandiri
Addini Yusmar UIN Mahmud Yunus Batusangkar
Khairiyah Khadijah Universitas Riau
Sri Wahyuni Universitas Islam Negeri Sultan Syarif Kasim Riau
Naufal Ibnu Salam Institut Pertanian Bogor

DOI: https://doi.org/10.29207/resti.v9i2.6333

Keywords: Problem-solving, krulik and rudnick method, forward chaining, certainty factor, confusion matrix

Abstract

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 recall of 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.

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