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Prediction of Agro Products Sales Using Regression Algorithm
American Journal of Data Mining and Knowledge Discovery
Volume 5, Issue 1, June 2020, Pages: 11-19
Received: Jun. 3, 2020; Accepted: Jun. 17, 2020; Published: Jul. 6, 2020
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Terungwa Simon Yange, Department of Mathematics/Statistics/Computer Science, University of Agriculture, Makurdi, Nigeria
Charity Ojochogwu Egbunu, Department of Mathematics/Statistics/Computer Science, University of Agriculture, Makurdi, Nigeria
Oluoha Onyekwere, Department of Computer Science, University of Nigeria, Nsukka, Nigeria
Kater Amos Foga, Department of Computer Science, University of Nigeria, Nsukka, Nigeria
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This study aimed at developing a system using support vector machine (SVM) that will forecast sales of farm products for an agricultural farm so that managers can take strategic decisions timely to better market the excess farm products which some by nature are perishable. The sales prediction model used SVMs and Fuzzy Theory. The implementation was done using Python Programming Language. The system comprised of three (3) modules: web interface, flask and the SVM Framework. To evaluate the result of the SVM model, the RBF neural network was used as a benchmark. Data of previous sales records from University of Agriculture Makurdi (UAM) farm was used to train and test the system. After training the network with data which covered the time period from 21st January, 2017 to 30th June, 2019, the remaining data which covered from 1st July 2019 up to the 31st December, 2019 was used to test and validate the forecasting performance of the system. The Forecasting Precision (FP) value for the SVM was 96.75% and that of the RBF neural network forecasting value was 90.55%. Analysis from the results shows that the forecasting system with SVM had a greater precision in the sales of agricultural products.
Prediction, Regression, Algorithm, Agricultural Products, Sales, SVM
To cite this article
Terungwa Simon Yange, Charity Ojochogwu Egbunu, Oluoha Onyekwere, Kater Amos Foga, Prediction of Agro Products Sales Using Regression Algorithm, American Journal of Data Mining and Knowledge Discovery. Vol. 5, No. 1, 2020, pp. 11-19. doi: 10.11648/j.ajdmkd.20200501.12
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This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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