Implementasi Metode MABAC dengan Pembobotan Entropy Dalam Sistem Pendukung Keputusan Proses Rekruitmen CIO - Siti Emalia Saqila; Amelia Hayatul; Agus Iskandar (STMIK Budi Darma, 2024)
This research aims to investigate and implement the MABAC (Multi-Attributive Border Approximation) method with weighting based on entropy in a decision support system (DSS) to recommend the most suitable Chief Information Officer (CIO) candidate. As an integral part of upper-level management, the selection of a CIO is a strategic decision that has a major impact on organizational performance. Therefore, the use of SPK in the CIO recruitment process can help organizations make more effective and rational decisions. The MABAC method is used because it is able to overcome situations of uncertainty and ambiguity in CIO recruitment decision making, which involves several interrelated attributes and has the potential to influence CIO performance. Entropy-based weighting is used to measure the level of uncertainty or randomness in attribute data, thereby providing accurate weights for each attribute in the decision-making process. This research uses empirical data from a number of CIO candidates who have various backgrounds and experiences. The data includes a variety of attributes such as education, work experience, technical expertise, and leadership skills. The MABAC method with entropy weighting was used to process this data, and the results were used to produce a ranking of the most suitable CIO candidates. The results of this research indicate that the use of the MABAC method with entropy weighting in the SPK can produce more accurate and reliable CIO recommendations. These results can assist recruiting teams and senior management in selecting the CIO who best fits the organization's needs. Apart from that, this research also identifies the attributes that are most influential in CIO recruitment decisions, so that it can help organizations in designing appropriate skills development or training programs for selected CIO candidates. Thus, this research makes an important contribution to the field of HR management and strategic decision making, especially in the context of CIO recruitment. The results of calculations in this research show that the alternative in the name of Eric Yahya is in first place with a value of 0.405. The results can be a valuable guide for organizations looking to improve their executive selection and recruitment processes