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Recommendation method for selecting the rice seeds based on group decision support system

IAES International Journal of Artificial Intelligence · Vol. 13 No. 3 (2024) · hlm. 2656–2665

DOI
10.11591/ijai.v13.i3.pp2656-2665
ISSN
2252-8938, 2089-4872
Terbit
2024-09-01
Penerbit
Institute of Advanced Engineering and Science
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

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.

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  • Mulawarman University
  • Universitas Teknologi Yogyakarta
  • STMIK Banjarbaru
  • Sekolah Tinggi Ilmu Kesehatan Harapan Ibu Jambi
  • Universitas Jambi
  • Bakrie University
  • Tarumanagara University
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Rekan penulisOrganisasiArtikel bersama
Budi RahmaniSTMIK Banjarbaru7
Heru IsmantoMusamus Merauke University7
Agus Qomaruddin MunirUniversitas Respati Yogyakarta6
Andri SyafriantoSTMIK El Rahma Yogyakarta6
Novianti PuspitasariMulawarman University5
Dyna Marisa KhairinaMulawarman University4
Ummul HairahMulawarman University4
Surya Eka PriyatnaUniversitas Islam Negeri Antasari Banjarmasin4
Hamdani HamdaniMulawarman University2
Andi TejawatiMulawarman University2
Heliza Rahmania HattaMulawarman University2
Henderi HenderiUniversitas Raharja2
Enny Itje SelaUniversitas Teknologi Yogyakarta1
Saucha DiwandariUniversitas Teknologi Yogyakarta1
Briyan Efflin SyahputraUniversitas Teknologi Yogyakarta1
Nathaniela Aptanta ParamaUniversitas Teknologi Yogyakarta1
Hugo ApriliantoSTMIK Banjarbaru1
Joan Angelina WidiansMulawarman University1
Ade Fiqri TjikoaMulawarman University1
Wulan SariAfiliasi tidak diketahui1
Ari SanjayaAfiliasi tidak diketahui1
Rudianto RudiantoAfiliasi tidak diketahui1
Rudy Agung NugrohoAfiliasi tidak diketahui1
Retno AryaniAfiliasi tidak diketahui1
Hetty ManurungMulawarman University1
Muhammad Fauzi ArifMulawarman University1
Iyut Jaya ToimsarAfiliasi tidak diketahui1
Silvia MeilinaSekolah Tinggi Ilmu Kesehatan Harapan Ibu Jambi1
Melda YenniSekolah Tinggi Ilmu Kesehatan Harapan Ibu Jambi1
Khairinal KhairinalUniversitas Jambi1
Emosda EmosdaUniversitas Jambi1
Vina Zahrotun KamilaMulawarman University1
Novianti PuspitasariMulawarman University1

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Sumber metadata: OAI-PMH (metadata jurnal) http://ijai.iaescore.com/index.php/IJAI/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Recommendation method for selecting the rice seeds based on group decision support system</dc:title>
	<dc:creator>Hamdani, Hamdani</dc:creator>
	<dc:creator>Wati, Masna</dc:creator>
	<dc:creator>Suprihanto, Didit</dc:creator>
	<dc:creator>Salsabila, Nur Maya</dc:creator>
	<dc:creator>Septiarini, Anindita</dc:creator>
	<dc:creator>Nurmadewi, Dita</dc:creator>
	<dc:creator>Mawardi, Viny Christanti</dc:creator>
	<dc:subject xml:lang="en-US">GDSS</dc:subject>
	<dc:subject xml:lang="en-US">Borda; Group decision; Recommendation; Rice seeds; TOPSIS</dc:subject>
	<dc:description xml:lang="en-US">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.</dc:description>
	<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
	<dc:contributor xml:lang="en-US">Universitas Mulawarman</dc:contributor>
	<dc:date>2024-09-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US"></dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ijai.iaescore.com/index.php/IJAI/article/view/23897</dc:identifier>
	<dc:identifier>10.11591/ijai.v13.i3.pp2656-2665</dc:identifier>
	<dc:source xml:lang="en-US">IAES International Journal of Artificial Intelligence (IJ-AI); Vol 13, No 3: September 2024; 2656-2665</dc:source>
	<dc:source>2252-8938</dc:source>
	<dc:source>2089-4872</dc:source>
	<dc:source>10.11591/ijai.v13.i3</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/view/23897/14074</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2024 Institute of Advanced Engineering and Science</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>