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Objectives: Food has been a major concern in the Philippines regarding production and utilization. The main purpose of this research is to develop a model to venture the future of food production and consumption. Methods/Analysis: This study explored using data mining technique using regression and cluster analysis to establish a new knowledge from a data set ranging from 1990 to 2013, where the data taken and extracted into a software readable formatfrom the Philippine Government repository like the PhilFSIS and PAGASA. This research utilized software such as MiniTab 13.20 and Weka 3.7to facilitate model generation. Findings: The data generated were analyzed and found out that only poultry products were not affected by the typhoons. Thisresult is considered to be unique in nature considering that the Philippines is the most visited strong typhoons in the world, and can affect the poultry production. In the model generated, a significant finding also reveals that ischolar_main crops, poultry products, and hog production increase if there is an increase of typhoons that enter the PAR. Finally, a theory was created based on the interpretation of the generated data from the data mining processes. Novelty/Improvement: These results only suggest that the authorities should look into the risk of declining of the production of other commodities and create a more climate resilient plan of production to sustain the future needs of the consumers. Further study must be conducted to establish the validity of the result of this study.

Keywords

Cluster Analysis, Climate Change, Food Security, Regression, Typhoon, Theory Development.
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