Principal Component Analysis (PCA) dalam Melihat Faktor-Faktor Mempengaruhi Perkembangan Ternak Ayam (Studi Kasus: Peternakan Ayam Mutiara Sani, Mitra PT Ciomas Adisatwa, Pekanbaru)

Abstract

The focus of this observation is to see which factors have the highest variance or can represent the factor data and which most influence broiler development. To obtain the desired information, principal component analysis (PCA) will be used to perform the reduction in this study. After analysis, it was found that of the 12 variables contained in the dataset, 1 variable was reduced and resulted in three factors that could represent the 11 variables. The dataset used in this study is data obtained by observation for approximately one month at Mutiara sani chicken farm. Of the 11 variables that affect the development of broiler chickens analyzed using PCA, 3 new factors were formed. Factor 1 is formed on four variables, namely variables (feed), 2(vitamin 1),3(vitamin 2), 7(vitamin 3), named Consumption Factor (47.164%). Factor 2 consists of variables 5(DOC), 6(temperature), 10(experience),named Crucial Factors (11.276%). Factor 3 consists of the variables 4(number of workers), 8(width of the cage),9(Educational status of the workforce), 11(age of the workforce, named Quality of Care Factor( 10.159%). The three new factors that were formed were able to explain the total variance (cumulative percent of variance) of 68.589%, which means that the three factors can affect the development of broiler weight by 68.589%, the rest may be caused by other factors that are not included in this analysis.