Implementasi algoritma principal component analysis dalam reduksi faktor yang mempengaruhi produksi susu sapi perah
Abstract
Many factors can affect the milk production of cows, namely the feed given, the technology used by farmers, and the number of cows owned by farmers. Due to the large number of external factors that can affect the amount of milk production, it is necessary to reduce variables that have less significant influence so that management can focus on the factors that have the most influence, in terms of variable reduction, the principal component analysis (PCA) statistical method can be used. This method is used to simplify the variables in the dataset by reducing their dimensions so that it is easier to interpret the data. Variable reduction using PCA produces two new components using three methods, namely cumulative sum of proportions, eigenvalue and scree plot. After PCA analysis using three methods, two new components were obtained, namely PC1 and PC2. One variable included in the new PC1 component is X6 because it has a value of more than 0.5 and there are two variables included in the new PC2 component, namely X4 and X5.
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