This study aims to analyze COVID-19 research articles from the Philippines, utilizing a combination of bibliometric analysis and topic modeling. The dataset, obtained from Scopus, includes various metadata fields such as authors, titles, publication year, source title, volume, issue, page information, citation count, affiliations, abstract, keywords, funding details, and document type.

This study delves into the comparative analysis of rainfed and irrigated palay (rice) volume of production in the Philippines, employing a multiple linear regression approach. The research utilizes data extracted from the Philippine Statistics Authority's 2012 Census of Agriculture and Fisheries. Palay production is a vital component of the Philippine agricultural sector, with both rainfed and irrigated cultivation methods playing significant roles in the country's food security and economic stability. By employing multiple linear regression, this study aims to identify the key factors influencing palay production under rainfed and irrigated conditions, and to discern the relative impacts of these factors on production volume.

This project analyzes factors influencing palay production in the Philippines using multiple linear regression in R. It explores various socio-economic and environmental variables to predict palay yield, also comparing factors affecting production of irrigated and rainfed palay.