Factor analysis of beef gravel quality using Principal Component Analysis (PCA)

Abstract

Factor analysis aims to reduce the amount of information from the original variable without losing important information. A factor is a collection of reduced variables. Several methods can be used in factor analysis, the most common of which are principal component analysis and maximum likelihood. The principal component analysis technique was used in this study. This technique was chosen because it better represents the purpose of the analysis than others. A case study of beef gravel is used to supplement the explanation of factor analysis using the Principal Component Analysis (PCA) technique. The goal of this study was to identify the most important factors influencing beef gravel quality to maintain product quality. The main factor is the volume of soaking water, and the second is the volume of soaking two dishes. These two factors have a cumulative variance proportion of 55%, indicating that they can influence the quality of the gravel. In contrast, the rest can be influenced by other factors not revealed in the research model.