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COMPARISON OF CERTAINTY FACTOR AND DEMPSTER SHAFER METHODS IN EXPERT SYSTEMS FOR IDENTIFYING FACIAL SKIN TYPES Fajar Maulana Yusuf; Andri Sukma Indrayana
ADVANCE INFORMATICS RESEARCH JOURNAL Vol. 2 No. 2 (2026): Advanced Informatics Research
Publisher : LKP Tematik Aperta Nusantara

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Abstract

The Tematik Aperta Nusantara (TAN) Course and Training Institution (LKP) offers various training programs aimed at enhancing participant competence. However, the process of determining the appropriate training program for prospective participants is currently conducted manually through interviews and initial assessments by staff, a method that is time-consuming and prone to subjectivity. This research aims to design and develop a web-based Decision Support System (DSS) to classify prospective training participants at LKP TAN using the *Profile Matching* method, thereby making the selection process more objective, efficient, and structured. The research methodology encompasses observation, interviews, literature review, and the development of a web-based system implementing the *Profile Matching* technique. Participant data is collected via registration and questionnaires, then processed based on five criteria: interest in the training field, basic computer skills, information technology experience, communication skills, and creativity. The results demonstrate that the developed system is capable of managing participant data, criteria data, and ideal training program profiles. It performs *Profile Matching* calculations—including GAP analysis, GAP weighting, *Core Factor* and *Secondary Factor* assessments, and final score computation. The system generates training program recommendations ranked by the level of compatibility between the participant's profile and the program's ideal profile. Consequently, the developed system assists LKP TAN in classifying prospective training participants more effectively, objectively, and through a computerized process.