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All Journal International Journal of Electrical and Computer Engineering
Kurnia Anggriani
University of Bengkulu, Indonesia
Computer Science & IT Electrical & Electronics Engineering

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Online Expert Systems For Bamboo Identification Using Case Based Reasoning Endina Putri Purwandari; Ariefa Primair Yani; Ramanda Sugraha; Kurnia Anggriani; Endang Widi Winarni
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (687.39 KB) | DOI: 10.11591/ijece.v7i5.pp2766-2772

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.
Co-Authors Ariefa Primair Yani Endang Widi Winarni Endina Putri Purwandari Ramanda Sugraha