Artificial Intelligence in Decision Support Systems for Job Promotions

Educational Personnel have an important role in supporting the success of education. Educational Personnel have a role in carrying out administration, management, development, supervision, and technical services to support the educational process in educational units. The declining performance of education personnel at the junior high school level in West Jakarta, particularly due to the ineffectiveness of the promotion system, demonstrates the need for an objective, data-driven assessment mechanism. Education personnel play a crucial role in the administration, management, and technical services of education, thus a transparent promotion system is essential. This study aims to develop a promotion recommendation model using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method integrated with artificial intelligence (AI) to improve the accuracy, objectivity, and efficiency of the decision-making process. The study involved 112 civil servant education personnel respondents from 53 junior high schools in eight sub-districts in West Jakarta, selected through multistage random sampling. Analysis was conducted using five main criteria: educational background, performance, technical skills, length of service, and work motivation. AI was used to automate normalization, weighting, and pattern analysis. The results showed that TOPSIS was able to produce an objective candidate ranking, with respondent R099 having the highest Closeness Coefficient (≈0.7704), making him the most suitable for promotion. The integration of TOPSIS and AI has been proven to increase analysis speed, reduce human bias, and provide more consistent and accurate recommendations for education staff promotion.