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IJSTR >> Volume 9 - Issue 3, March 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Diagnostic Analysis Of Rice Productivity Using Classification Based On Shannon And Renyi Entropy

[Full Text]

 

AUTHOR(S)

Fajar Delli Wihartiko, Eneng Tita Tosida, Ruhul Amin

 

KEYWORDS

Shannon Entropy, Renyi Entropy, Diagnostic Analysis, Rice Productivity

 

ABSTRACT

Rice is the main commodity in Indonesia both for consumption and in terms of production. The increasing number of Indonesian population resulting in increased demand for rice is a problem that must be faced by the government to maintain national food stability. Currently Indonesian rice productivity data is available at the Central Statistics Agency and at the Ministry of Agriculture. The data is used in descriptive and diagnostic analysis. Descriptive analysis uses clustering, data visualization and entropy. The diagnostic process uses an entropy-based classification to see factors of production. The entropy function used is Shannon and Renyi Entropy. The results of using entropy in the description analysis show that production attributes have a higher level of uniformity. The results of entropy in the classification show that there are differences in the decision tree that results from Shannon and Renyi entropy. In this case Renyi Entropy has better accuracy..

 

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