The purpose of this scientific paper is to design and implement a knowledge-based expert system to assist students in determining their major specializations at Vocational High Schools (SMK) more objectively and accurately. A major problem frequently faced by SMK students is the mismatch in department selection caused by a lack of understanding regarding their own potential and the specific criteria of each competency. To address this issue, the system was developed using the Forward Chaining method as the inference engine. This method operates in a data-driven manner, beginning with the collection of facts such as interests, academic abilities, and psychological aspects, which are then matched against a Knowledge Base consisting of IF-THEN logical rules. Based on system testing results, the inference engine is capable of processing the list of facts to generate a specialization diagnosis for SMK students and provide the most relevant departmental recommendations, such as Computer and Network Engineering (TKJ), Accounting, Office Automation and Governance (OTKP), or Marketing. The research results indicate that the implementation of the Forward Chaining method is effective in accelerating the decision-making process and minimizing placement errors. This expert system is expected to serve as a tool for Guidance and Counseling (BK) teachers in providing appropriate career direction for students based on structured empirical data.
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