Implementation of Certainty Factor Method in a Web-Based Expert System for Abacus Student Level Assessment

Abstract

The placement of new students into appropriate program levels is a critical factor in the effectiveness of mental arithmetic education through the abacus method. At SEMPOA SIP Binjai Mas, this process has historically been conducted manually, relying heavily on the subjective intuition of instructors, which often results in inconsistent decision-making and assessment bias. Furthermore, the inherent uncertainty in student performance during diagnostic tests often caused by nervousness or incomplete understanding further complicates accurate classification. This research aims to design and implement a web-based expert system using the Certainty Factor (CF) method to provide a standardized, objective, and mathematically grounded recommendation for student placement. The system was developed using the Waterfall methodology and utilizes 11 validated capability indicators to categorize students into two primary levels: Junior and Foundation. The Certainty Factor method was specifically employed to quantify uncertainty and manage the degrees of confidence in student performance by integrating expert knowledge (MB and MD values) with user-provided observations. Empirical validation through a case study demonstrated high precision, yielding a 99.73% confidence level for program placement in a scenario where manual assessment might prove ambiguous. Black-box testing further confirmed that all system functionalities are 100% valid and meet operational requirements. The implementation of this expert system significantly mitigates assessment subjectivity, enhances administrative efficiency through real-time data access, and establishes a transparent, professional assessment framework for the institution.