Indonesia has significant fisheries potential due to its vast waters. Its abundant fishery resources have strong export potential. However, export activities often face challenges that cause export volumes to fluctuate. This fluctuation is influenced by various factors. These factors can be minimized using statistical methods such as Principal Component Analysis (PCA) and Factor Analysis. This study includes data characterization for each variable and testing PCA and factor analysis assumptions, including multivariate normality testing, independence testing (Bartlett's test), sampling adequacy (KMO test), anti-image correlation testing, PCA testing, and factor analysis. The results indicate that the percentage contribution of fisheries to GDP, the number of coastal villages with disaster mitigation facilities, and the average daily per capita calorie consumption from fish are relatively less dispersed and not highly variable around the mean. Additionally, all data meet the assumptions, and the sample size is adequate. Factors such as aquaculture pond production and the percentage contribution of fisheries to GDP sufficiently explain the data variations.
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