#install.packages("foreign")
library(foreign)
#install.packages("stats")
library(stats)
library(readxl)
## Warning: package 'readxl' was built under R version 4.4.3
#====RANCANGAN ACAK LENGKAP====
#masukkan data
# Membuat data suhu (perlakuan)
Suhu <- c(
rep(40, 5),
rep(50, 5),
rep(60, 5),
rep(70, 5),
rep(80, 5),
rep(90, 5)
)
# Membuat data ulangan (1–5 untuk tiap suhu)
Ulangan <- rep(1:5, times = 6)
# Memasukkan data hasil pengamatan (sesuai tabel)
Kadar.Antosianin <- c(
19.4, 32.6, 27.0, 32.1, 33.0, # Suhu 40
17.7, 24.8, 27.9, 25.2, 24.3, # Suhu 50
17.0, 19.4, 9.1, 11.9, 15.8, # Suhu 60
20.7, 21.0, 20.5, 18.8, 18.6, # Suhu 70
14.3, 14.4, 11.8, 11.6, 14.2, # Suhu 80
17.3, 19.4, 19.1, 16.9, 20.8 # Suhu 90
)
# Membentuk data frame
data.antosianin <- data.frame(
Suhu = as.factor(Suhu),
Ulangan = as.factor(Ulangan),
Kadar.Antosianin = Kadar.Antosianin
)
# Menampilkan data
print(data.antosianin)
## Suhu Ulangan Kadar.Antosianin
## 1 40 1 19.4
## 2 40 2 32.6
## 3 40 3 27.0
## 4 40 4 32.1
## 5 40 5 33.0
## 6 50 1 17.7
## 7 50 2 24.8
## 8 50 3 27.9
## 9 50 4 25.2
## 10 50 5 24.3
## 11 60 1 17.0
## 12 60 2 19.4
## 13 60 3 9.1
## 14 60 4 11.9
## 15 60 5 15.8
## 16 70 1 20.7
## 17 70 2 21.0
## 18 70 3 20.5
## 19 70 4 18.8
## 20 70 5 18.6
## 21 80 1 14.3
## 22 80 2 14.4
## 23 80 3 11.8
## 24 80 4 11.6
## 25 80 5 14.2
## 26 90 1 17.3
## 27 90 2 19.4
## 28 90 3 19.1
## 29 90 4 16.9
## 30 90 5 20.8
# Membuat faktor perlakuan (Metode)
Metode <- c(
rep("A", 15),
rep("B", 15),
rep("C", 15)
)
# Membuat faktor ulangan (1–15 untuk tiap metode)
Ulangan <- rep(1:15, times = 3)
# Memasukkan nilai data sesuai tabel
Nilai <- c(
# Metode A
73, 89, 82, 43, 80, 73, 66, 60, 45, 93, 36, 77, NA, NA, NA, # isi NA jika tidak ada data
# Metode B
88, 78, 48, 91, 51, 85, 74, 77, 31, 78, 62, 76, 96, 80, 56,
# Metode C
68, 79, 56, 91, 71, 71, 87, 41, 59, 68, 53, 79, 15, NA, NA
)
# Membentuk data frame
data.metode <- data.frame(
Metode = as.factor(Metode),
Ulangan = as.factor(Ulangan),
Nilai = Nilai
)
# Melihat struktur data
print(data.metode)
## Metode Ulangan Nilai
## 1 A 1 73
## 2 A 2 89
## 3 A 3 82
## 4 A 4 43
## 5 A 5 80
## 6 A 6 73
## 7 A 7 66
## 8 A 8 60
## 9 A 9 45
## 10 A 10 93
## 11 A 11 36
## 12 A 12 77
## 13 A 13 NA
## 14 A 14 NA
## 15 A 15 NA
## 16 B 1 88
## 17 B 2 78
## 18 B 3 48
## 19 B 4 91
## 20 B 5 51
## 21 B 6 85
## 22 B 7 74
## 23 B 8 77
## 24 B 9 31
## 25 B 10 78
## 26 B 11 62
## 27 B 12 76
## 28 B 13 96
## 29 B 14 80
## 30 B 15 56
## 31 C 1 68
## 32 C 2 79
## 33 C 3 56
## 34 C 4 91
## 35 C 5 71
## 36 C 6 71
## 37 C 7 87
## 38 C 8 41
## 39 C 9 59
## 40 C 10 68
## 41 C 11 53
## 42 C 12 79
## 43 C 13 15
## 44 C 14 NA
## 45 C 15 NA
#ANOVA
#Cara 1
#data 1
anova.antosianin<-lm(Kadar.Antosianin~Suhu, data.antosianin)
anova(anova.antosianin)
## Analysis of Variance Table
##
## Response: Kadar.Antosianin
## Df Sum Sq Mean Sq F value Pr(>F)
## Suhu 5 847.05 169.409 14.37 1.485e-06 ***
## Residuals 24 282.93 11.789
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#data 2
anova.metode <- lm(Nilai~Metode, data.metode)
anova(anova.metode)
## Analysis of Variance Table
##
## Response: Nilai
## Df Sum Sq Mean Sq F value Pr(>F)
## Metode 2 335.4 167.68 0.4647 0.6319
## Residuals 37 13349.7 360.80
#Cara 2
#data 1
ujianova = aov(Kadar.Antosianin~Suhu, data.antosianin)
ujianova
## Call:
## aov(formula = Kadar.Antosianin ~ Suhu, data = data.antosianin)
##
## Terms:
## Suhu Residuals
## Sum of Squares 847.0467 282.9280
## Deg. of Freedom 5 24
##
## Residual standard error: 3.433463
## Estimated effects may be unbalanced
summary(ujianova)
## Df Sum Sq Mean Sq F value Pr(>F)
## Suhu 5 847.0 169.41 14.37 1.48e-06 ***
## Residuals 24 282.9 11.79
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#data 2
ujianova = aov(Nilai~Metode, data =data.metode)
ujianova
## Call:
## aov(formula = Nilai ~ Metode, data = data.metode)
##
## Terms:
## Metode Residuals
## Sum of Squares 335.353 13349.747
## Deg. of Freedom 2 37
##
## Residual standard error: 18.99484
## Estimated effects may be unbalanced
## 5 observations deleted due to missingness
summary(ujianova)
## Df Sum Sq Mean Sq F value Pr(>F)
## Metode 2 335 167.7 0.465 0.632
## Residuals 37 13350 360.8
## 5 observations deleted due to missingness