Sistem Pendukung Keputusan Dalam Memilih Bibit Kedelai Menggunakan Kombinasi Metode TOPSIS dan ROC - Heni Sulistiani; Untoro Adji; Sufiatul Maryana; Setiawansyah (STMIK Budi Darma, 2023)
To increase agricultural yields, seed selection is very important, one of which is in soybean plants, the problem that arises is the absence of a decision support system model in determining good soybean seeds for soybean farmers. So, farmers only choose existing soybean seeds based on the recommendations of fellow soybean farmers. This study aims to conduct a combination of ROC and TOPSIS can help in managing the complexity of determining agricultural seeds more efficiently. This is because ROC helps in sequencing variables, whereas TOPSIS helps in choosing the optimal alternative. This combination allows stakeholders to make more informed and rational decisions. The ROC method is a multivariate analysis technique used to analyze data that involves sorting or ranking variables measured in a group or population. ROC can be an effective analytical tool in helping stakeholders optimize their strategies or policies in a variety of situations and industries that require a deep understanding of data sequencing or ranking. The Technique for Order Preference by Similarity to Ideal Solution method or often known as the TOPSIS method is a decision-making analysis approach used to assist stakeholders in evaluating alternatives based on a number of predetermined criteria. The combination of ROC and TOPSIS can provide a deeper understanding of the structure of relationships between variables and their impact on alternative rankings. Based on the results of the ranking of agricultural seeds that get 1st Rank, namely Grobongan with a value of 0.54047, 2nd Rank, namely Anjasmoro with a value of 0.5, 3rd Rank, namely Detap 1 with a value of 0.43828, 4th Rank, Dena 1 with a value of 0.43457, and 5th Rank, namely Dering 1 with a value of 0.40553.