Implementation of a Rule-Based Expert System and Weighted Scoring Method in Developing a Student and Alumni Information System for Sustainable Graduate Competency Mapping - Adi Fitrianto; Sahla Rizki Farhanna (International Journal of Technology and Education Research, 2026)
The management of student activity data scattered across numerous categories and the manual, subjective assessment of graduate competencies make student competency profiles difficult to standardize, compare, and verify. This study develops a Student and Alumni Information System that manages activity data, alumni data, and online CVs while mapping graduate competencies automatically, objectively, and auditably by applying a rule-based expert system and a weighted scoring method based on Simple Additive Weighting (SAW). The system was built using the Laravel 12 framework and a MySQL database with the Prototype development model. The competency engine operates deterministically: verified student activities are normalized, matched against a competency catalog (soft skills through a category matrix and technical skills through keywords), and then scored by multiplying base points with role, level, output, and verification multipliers. The scores are aggregated using a diminishing returns mechanism and enriched with an academic bonus (GPA) to determine competency levels (from Developing to Expert), along with a confidence level and a traceable evidence trail. Testing was carried out using black box testing and validation of the scoring results against student affairs expert judgment. The results show that the system produces consistent and verified competency profiles to support the generation of online CVs and Diploma Supplements (SKPI), thereby supporting sustainable competency development and graduate competitiveness (sustainable employability).