Salsabila, Nur Maya
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Recommendation method for selecting the rice seeds based on group decision support system Hamdani, Hamdani; Wati, Masna; Suprihanto, Didit; Salsabila, Nur Maya; Septiarini, Anindita; Nurmadewi, Dita; Mawardi, Viny Christanti
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp2656-2665

Abstract

In this paper, we provide group recommendations based on each decision makers (DMs) in choosing the best type of rice for replanting. This group decision support system (GDSS) aims to guide stakeholders who have a role in selecting rice types. In this method, we propose using technique for order preference by similarity to ideal solution (TOPSIS) to rank each DM, Borda to rank in groups, and then test it using Spearman's rank correlation to measure the relationship between system results and the method applied. The results of this study show that DM1 ranks highest in selecting Gelagai rice seeds with a preference of 0.7786. Then DM2 ranked highest with Ekor Payau rice seeds in preference 0.6529. Meanwhile, DM3 ranked highest in Gelagai rice seeds with a selection of 0.7728. The final group voting system uses Borda, where Gelagai rice seeds occupy the highest rank with the most accumulated votes from each DMs. The best option or the highest rating based on the assessment of the three DMs, DM1 as a farmer is the first rank A10 Gelagai with a score of Borda 26 in the decision group selection of superior rice seeds.