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Online Expert Systems For Bamboo Identification Using Case Based Reasoning

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 7 No. 5 (2017)

DOI
10.11591/ijece.v7i5.pp2766-2772
ISSN
2088-8708, 2088-8708
Published
2017-10-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

Bamboo is a typical plant that thrives in tropical countries like Indonesia. The diversity of bamboo species makes difficult to classified, then requiring the expertise from specialist who understands deeply about bamboo characteristics. The paper purpose to (1) adopts the bamboo expert knowledge into bamboo criteria of expertise; (2) implementing Case Based Reasoning method in online expert system for bamboo identification in Bengkulu Province; and (3) determined the identification accuracy of bamboo using expert systems. The system uses Case Based Reasoning with four main steps: retrieve, reuse, revise, and retain. Bamboo expert identify bamboo criteria into 6 morphology, 31 features, and 219 attributes as an input system. The results showed that the Case Based Reasoning method has high accuracy for identifying the bamboo species and can solve the problem of bamboo identification as a new case based on old case that stored in the base case.

Collaboration network of the authors

5 authors · 10 co-authorship links

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  • University of Bengkulu
  • Different organisations
  • Same organisation
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Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Online Expert Systems For Bamboo Identification Using Case Based Reasoning</dc:title><dc:creator>Purwandari, Endina Putri</dc:creator><dc:creator>Yani, Ariefa Primair</dc:creator><dc:creator>Sugraha, Ramanda</dc:creator><dc:creator>Anggriani, Kurnia</dc:creator><dc:creator>Widi Winarni, Endang</dc:creator><dc:description>&lt;jats:p&gt;Bamboo is a typical plant that thrives in tropical countries like Indonesia. The diversity of bamboo species makes difficult to classified, then requiring the expertise from specialist who understands deeply about bamboo characteristics. The paper purpose to (1) adopts the bamboo expert knowledge into bamboo criteria of expertise; (2) implementing Case Based Reasoning method in online expert system for bamboo identification in Bengkulu Province; and (3) determined the identification accuracy of bamboo using expert systems. The system uses Case Based Reasoning with four main steps: retrieve, reuse, revise, and retain. Bamboo expert identify bamboo criteria into 6 morphology, 31 features, and 219 attributes as an input system. The results showed that the Case Based Reasoning method has high accuracy for identifying the bamboo species and can solve the problem of bamboo identification as a new case based on old case that stored in the base case.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2017-10-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v7i5.pp2766-2772</dc:identifier><dc:identifier>10.11591/ijece.v7i5.pp2766-2772</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 7 No 5 (2017); 2766</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/8231/6955</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>