Praktikum Analisis Multivariat

# https://www.kaggle.com/datasets/nbbndavid/apple-quality-dataset
# data
data <- data.frame(
  Kualitas = c("bad", "bad", "good", "bad", "bad", "bad", "bad", "good", "good", "bad", "good", "bad", "bad", "bad", "bad"),
  Lama_membusuk = c(11.6, 10.5, 20.2, 6.6, 17.1, 19.3, 7, 19.7, 11.3, 11.1, 25, 15.6, 12.6, 12.8, 11.1),
  Berat = c(148.9, 155, 196.3, 153.9, 150.8, 162.5, 197, 149.1, 241.1, 162.9, 203.2, 196.8, 178.8, 165.8, 136.8),
  Tingkat_kematangan = c(1.39, 2.86, -2.1, 0.84, -0.98, -0.73, -0.89, -1.3, 0.07, -1.25, 0.41, -0.08, -0.36, -1.36, -0.87)
)

# konversi ke faktor
data$Kualitas <- as.factor(data$Kualitas)

# analisis faktor 
model <- manova(cbind(Berat, Lama_membusuk) ~ Kualitas * Tingkat_kematangan, data = data)
summary(model, test = "Wilks")

##                             Df   Wilks approx F num Df den Df  Pr(>F)  
## Kualitas                     1 0.39918   7.5257      2     10 0.01014 *
## Tingkat_kematangan           1 0.95147   0.2550      2     10 0.77977  
## Kualitas:Tingkat_kematangan  1 0.79946   1.2542      2     10 0.32658  
## Residuals                   11                                         
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1