Sistem Pendukung Keputusan Rekomendasi Objek Wisata Menerapkan Metode MABAC dan Pembobotan ROC - Fifto Nugroho; Agung Triayudi; Mesran Mesran (Universitas Budi Darma, 2023)
North Sumatra possesses abundant potential for tourist attractions, yet achieving the optimal selection of these attractions poses a challenge. Therefore, a decision support system is required to aid in the decision-making process for choosing the most suitable tourist attractions. In this study, the Multi Atributive Border Approximation Area Comparison (MABAC) method is employed to rank tourist attractions based on predefined criteria. MABAC combines geometric approaches with boundary approximation area comparison analysis to calculate priority scores for each tourist attraction. Additionally, the Rank Order Centroid (ROC) method is used to assign weights to the identified criteria. This research reveals various issues in the selection of tourist attractions in North Sumatra, such as complex criteria, variations in criteria weights, and insufficient tools to address these challenges. The primary objective of this study is to develop a decision support system capable of assisting stakeholders in selecting tourist attractions aligned with their preferences and objectives. The outcome of this research is the development of an efficient decision support system to aid in the selection of tourist attractions in North Sumatra. This system reduces subjectivity in decision-making, provides more accurate ranking based on established criteria, and assists stakeholders in understanding the process of selecting tourist attractions in a more transparent manner. The implications of this research include enhancing the quality of decision-making in the tourism industry and optimizing the utilization of tourist attraction potential in North Sumatra. As for the tourism recommendation with the highest rank, alternative 3 is obtained with a value of 0.6343, namely Paropo natural tourism.