Kombinasi Metode MEREC dan TOPSIS dalam Seleksi Penerimaan Calon Karyawan Baru - Ilham Nasul Fathon Muhaji. P; Adhie Thyo Priandika (PT. Tech Cart Press, 2026)
The employee candidate selection process in many companies is still often carried out manually, resulting in decision-making that is subjective, inconsistent, and ineffective, especially when having to evaluate many applicants based on various criteria simultaneously. This situation makes it difficult for companies to determine the best candidate objectively and accurately. Therefore, this study aims to develop a Decision Support System (DSS) in the selection of new employee candidates by combining the MEREC (Method based on the Removal Effects of Criteria) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methods. The MEREC method is used to determine the weight of criteria objectively based on the influence of each criterion on the change in alternative performance, while the TOPSIS method is used to rank prospective employees based on their closeness to the positive ideal solution and their distance from the negative ideal solution. The criteria used in this study include education, work experience, technical skills, communication, and age. The results of the study indicate that the proposed method combination is able to produce a more objective, systematic, and accurate employee selection process. Based on the ranking results, alternative A7-IP obtained the highest preference value of 0.9945 and ranked first, followed by A5-EK with a value of 0.9427 in second place, and A1-AR with a value of 0.8946 in third place. The application of the MEREC and TOPSIS methods also successfully increased consistency and reduced subjectivity in the employee selection decision-making process.