QUALITY OF RESEARCH RESULTS IN AGRO-ECONOMY BY DATA MINING

Gordana Vukelić; Slobodan Stanojević; Zorica Anđelić

doi:10.5937/ekoPolj1504137V

Authors

Gordana Vukeli?, PhD Beogradska bankarska akademija, Fakultet za bankarstvo, osiguranje i fnansije, Belgrade
Slobodan Stanojevi?, PhD Univerzitet privredna akademija u Novom Sadu, Fakultet za mandžment, ekonomiju i fnansije, Belgrade
Zorica An?eli?, M.A. VCC Akademija

DOI:

https://doi.org/10.5937/ekoPolj1504137V

Keywords:

machine studies, data mining, prediction, classifcation, supervised discrimination analysis, decision tree, effectiveness of agro-research.

Abstract

Data Mining (DM) through data in agroeconomy is a scientifc method that enables researchers not to go through set research scenarioes that are predetermined assumptions and hypotheses on the basis of insignifcant atributes. On the contrary, by data mining detection of these atributes is made possible, in general, those hiden facts that enable setting a hypothesis. The DM method does this by an iterative way, including key atributes and factors and their influence on the quality of agro-resources. The research was conducted on a random sample, by analyzing the quality of eggs. The research subject is the posibility of classifying and predicting signifcant variablesatributes that determine the level of egg quality. The research starts from the use of Data Mining, as an area of machine studies, which signifcantly helps researchers in optimizing research. The applied methodology during research includes analyticalsintetic procedures and methods of Data Mining, with a special focus on using Supervised linear discrimination analysis and the Decision Tree. The results indicate significant posibilities of using DM as an additional analytical procedure in performing agroresearch and it can be concluded that it contributes to an improvement in effectiveness and validity of process in performing these researches.

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