Rice is a staple in every Filipino home where it is eaten three times a day or sometimes more. Luzon is the top producer of rice for the past years among the other two island groups. Rice plays a critical role in food security. This is one of the importance of rice forecasting. This study explores the possibility of using spatial data and temporal data on forecasting the production of rice at the same time. A Spatio-temporal Forecasting model is used to forecast the quarterly harvest of each of the seven rice producing regions of Luzon. This enables the gathered data to be utilized and manipulated for rice production forecasting. The effect of spatial correlations on the prediction accuracy of spatial forecasting is explored. The study showed that Spatio-temporal forecasting model is better than the most commonly used ARIMA forecasting.
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19 December 2019
PROCEEDINGS OF THE 8TH SEAMS-UGM INTERNATIONAL CONFERENCE ON MATHEMATICS AND ITS APPLICATIONS 2019: Deepening Mathematical Concepts for Wider Application through Multidisciplinary Research and Industries Collaborations
29 July–1 August 2019
Yogyakarta, Indonesia
Research Article|
December 19 2019
Forecasting rice production in Luzon using integrated spatio-temporal forecasting framework Free
Jackie D. Urrutia;
1
Associate Professor, Department of Mathematics and Statistics, College of Science, Polytechnic University of the Philippines
, Philippines
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Joshua Sy Bedaa;
2
Polytechnic University of the Philippines
, Philippines
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Chloe Bernice V. Combalicer;
2
Polytechnic University of the Philippines
, Philippines
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Francis Leo T. Mingo
3
Faculty Member, Polytechnic University of the Philippines Quezon City Branch
, Philippines
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Jackie D. Urrutia
1
Joshua Sy Bedaa
2
Chloe Bernice V. Combalicer
2
Francis Leo T. Mingo
3
1
Associate Professor, Department of Mathematics and Statistics, College of Science, Polytechnic University of the Philippines
, Philippines
2
Polytechnic University of the Philippines
, Philippines
3
Faculty Member, Polytechnic University of the Philippines Quezon City Branch
, Philippines
AIP Conf. Proc. 2192, 090014 (2019)
Citation
Jackie D. Urrutia, Joshua Sy Bedaa, Chloe Bernice V. Combalicer, Francis Leo T. Mingo; Forecasting rice production in Luzon using integrated spatio-temporal forecasting framework. AIP Conf. Proc. 19 December 2019; 2192 (1): 090014. https://doi.org/10.1063/1.5139184
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