#TM 4 Komputasi Statistika
#PACKAGES
library(car)
## Warning: package 'car' was built under R version 4.5.3
## Loading required package: carData
## Warning: package 'carData' was built under R version 4.5.3
library(agricolae)
## Warning: package 'agricolae' was built under R version 4.5.3
#Memanggil Data
data=read.table(file.choose(), header=T, dec = ",")
data
## tablet pelarut Data
## 1 1 1 46.18
## 2 1 2 54.54
## 3 1 3 56.63
## 4 2 1 57.69
## 5 2 2 71.57
## 6 2 3 81.51
## 7 3 1 48.61
## 8 3 2 51.01
## 9 3 3 80.02
#Pendefinisian Variabel
data$tablet=factor(data$tablet,levels=1:3,labels=c("CDR","Redoxon","Enervon-C"))
data$pelarut=factor(data$pelarut,levels=1:3,labels=c("Air Biasa","Air Soda","Air kelapa"))
data
## tablet pelarut Data
## 1 CDR Air Biasa 46.18
## 2 CDR Air Soda 54.54
## 3 CDR Air kelapa 56.63
## 4 Redoxon Air Biasa 57.69
## 5 Redoxon Air Soda 71.57
## 6 Redoxon Air kelapa 81.51
## 7 Enervon-C Air Biasa 48.61
## 8 Enervon-C Air Soda 51.01
## 9 Enervon-C Air kelapa 80.02
#Normalitas per Jenis Pelarut
for(j in levels(data$pelarut)){
cat("\nUji Normalitas untuk Jenis Pelarut:", j, "\n")
print(shapiro.test(data$Data[data$pelarut==j]))
}
##
## Uji Normalitas untuk Jenis Pelarut: Air Biasa
##
## Shapiro-Wilk normality test
##
## data: data$Data[data$pelarut == j]
## W = 0.89987, p-value = 0.3851
##
##
## Uji Normalitas untuk Jenis Pelarut: Air Soda
##
## Shapiro-Wilk normality test
##
## data: data$Data[data$pelarut == j]
## W = 0.87434, p-value = 0.3079
##
##
## Uji Normalitas untuk Jenis Pelarut: Air kelapa
##
## Shapiro-Wilk normality test
##
## data: data$Data[data$pelarut == j]
## W = 0.79474, p-value = 0.102
# Normalitas per Merek Tablet
for(i in levels(data$tablet)){
cat("\nUji Normalitas untuk Merek Tablet:", i, "\n")
print(shapiro.test(data$Data[data$tablet==i]))
}
##
## Uji Normalitas untuk Merek Tablet: CDR
##
## Shapiro-Wilk normality test
##
## data: data$Data[data$tablet == i]
## W = 0.89286, p-value = 0.3631
##
##
## Uji Normalitas untuk Merek Tablet: Redoxon
##
## Shapiro-Wilk normality test
##
## data: data$Data[data$tablet == i]
## W = 0.99096, p-value = 0.8182
##
##
## Uji Normalitas untuk Merek Tablet: Enervon-C
##
## Shapiro-Wilk normality test
##
## data: data$Data[data$tablet == i]
## W = 0.80695, p-value = 0.1312
#Homogenitas variansi
leveneTest(Data~pelarut, center=mean, data=data)
## Levene's Test for Homogeneity of Variance (center = mean)
## Df F value Pr(>F)
## group 2 1.9806 0.2185
## 6
leveneTest(Data~tablet, center=mean, data=data)
## Levene's Test for Homogeneity of Variance (center = mean)
## Df F value Pr(>F)
## group 2 2.4902 0.1632
## 6
#Uji ANOVA
anava2arah <- function(y, A, B){
a <- nlevels(A); b <- nlevels(B)
N <- length(y); n <- N/(a*b)
FK <- sum(y)^2/N
JKT <- sum(y^2) - FK
JK_A <- sum(tapply(y, A, sum)^2)/(b*n) - FK
JK_B <- sum(tapply(y, B, sum)^2)/(a*n) - FK
JKsel <- sum(tapply(y, list(A,B), sum)^2)/n - FK
JK_AB <- JKsel - JK_A - JK_B
JKG <- JKT - JKsel
db <- c(a-1, b-1, (a-1)*(b-1), a*b*(n-1), N-1)
JK <- c(JK_A, JK_B, JK_AB, JKG, JKT)
KT <- JK/db
F <- c(KT[1:2]/KT[3], NA, NA, NA)
p <- c(pf(F[1:2], db[1:2], db[3], lower.tail=FALSE), NA, NA, NA)
data.frame(Sumber=c("Tablet","Pelarut","Tablet*Pelarut","Galat","Total"), db=db, JK=JK, KT=KT, F_hitung=F, p_value=p)
}
anava2arah(y=data$Data, A=data$tablet, B=data$pelarut)
## Sumber db JK KT F_hitung p_value
## 1 Tablet 2 479.9575 239.97874 4.269572 0.10176166
## 2 Pelarut 2 733.9193 366.95964 6.528748 0.05499073
## 3 Tablet*Pelarut 4 224.8270 56.20674 NA NA
## 4 Galat 0 0.0000 NaN NA NA
## 5 Total 8 1438.7038 179.83797 NA NA
uji_anava=aov(Data~tablet+pelarut,data=data)
anova(uji_anava)
## Analysis of Variance Table
##
## Response: Data
## Df Sum Sq Mean Sq F value Pr(>F)
## tablet 2 479.96 239.98 4.2696 0.10176
## pelarut 2 733.92 366.96 6.5287 0.05499 .
## Residuals 4 224.83 56.21
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1