entrAN ANALYSIS OF PESTICIDE USE FOR COTTON PRODUCTION THROUGH DATA MINING: THE CASE OF NAZILLIAN ANALYSIS OF PESTICIDE USE FOR COTTON PRODUCTION THROUGH DATA MINING: THE CASE OF NAZILLI

Year 2018, Volume: 19 Issue: 3, 732 - 747, 01.09.2018

Zehra Burdur Canan Eren Atay

Abstract

Data mining involves certain methods of obtaining or inferring meaningful and otherwise-unknown information from the data. With the increasing significance of precision agricultural practices, farmers have become inclined to be engaged in a more conscious strategy of agriculture. Farmers use pesticides to destroy a disease or other hazard on their plants. Nevertheless, it has been learned over time that pesticides have harmful effects on human health and the environment. Although many farmers are aware of the risks of excessive use of agricultural pesticides, they still use them to get a faster yield and to maximize financial gain or minimize financial loss. Data received from Aydın Nazilli District Directorate of Agriculture was carefully organized and evaluated with the classification algorithms in the SPSS Clementine software. C5.0 and CR&T algorithms were employed in this study. It was thereby observed that, contrary to the conventional wisdom of most farmers, the excessive use of pesticides actually leads to a decrease in the yield obtained from the product, proportional to the measured dose.

Keywords

Data mining, agriculture, decision tree, C5.0 algorithm, CR&T algorithm

References

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