Speakers -

Abstract

Inadequate food production has been an immediate concern that the country is trying to address, where farmers use fertilizers in their farms to increase their agricultural production. However, if fertilizer application is poorly managed, it will result in the opposite instead of increasing production. Therefore, the efficient use of fertilizer is critical and dramatically impacts crop production. Thus, this study aims to show the Philippines' crop production pattern, specifically in rainfed and irrigated palay, white, and yellow corn. Moreover, this also indicates which fertilizer will maximize crop production and seek the most applicable model for forecasting future crop production. Three predictive techniques were used: canopy clustering, Apriori association rule mining, and time series forecasting models. Results reveal that all regions produce a low volume of rainfed rice. The canopy clustering shows the pattern leading to Region III's high production of irrigated rice. Also, Region II, Region X, and Region XII have a high volume of yellow corn production. Lastly, clustering results on white corn show Region VII has a Mid area harvested but shows a low production volume. In contrast, Region X has a low area harvested and managed to have a Mid-production volume. The association of fertilizers to the volume of production shows that low Ammophos leads to a lower volume of production, and low Ammosul is not associated with a low volume of production; hence, a combination of low Ammosul and low Ammophos leads to a low volume of production. The forecasting methods' linear regression, Gaussian processes, and SMOreg are all applicable in predicting the regions' production volume, whereas the SMOreg has the least MAE of 8.90% for Region VI.