library(readxl)
Data_Uji_Fisikokimia_R<- read_excel("D:/SKRIPSI ANGGUN/Data Uji Fisikokimia R.xlsx")
Data_Uji_Fisikokimia_R$Konsentrasi_Starter<- as.factor(Data_Uji_Fisikokimia_R$Konsentrasi_Starter)
Data_Uji_Fisikokimia_R$Lama_Fermentasi<- as.factor(Data_Uji_Fisikokimia_R$Lama_Fermentasi)
Data_Uji_Fisikokimia_R$pH_Kefir<- as.numeric(Data_Uji_Fisikokimia_R$pH_Kefir)
library(permuco)
Hasil_anova <- aovperm(pH_Kefir~Konsentrasi_Starter*Lama_Fermentasi, data= Data_Uji_Fisikokimia_R, np= 10000)
summary(Hasil_anova)
library(permuco)
Hasil_anova <- aovperm(pH_Kefir~Konsentrasi_Starter+Lama_Fermentasi, data= Data_Uji_Fisikokimia_R, np= 10000)
summary(Hasil_anova)
library(rcompanion)
res_posthoc_Konsentrasi_Starter <- pairwisePermutationTest(pH_Kefir~Konsentrasi_Starter, data= Data_Uji_Fisikokimia_R, method = "fdr")
print(res_posthoc_Konsentrasi_Starter)
## Comparison Stat p.value p.adjust
## 1 0.05 - 0.1 = 0 3.194 0.001404 0.002106
## 2 0.05 - 0.15 = 0 3.285 0.001018 0.002106
## 3 0.1 - 0.15 = 0 2.879 0.003987 0.003987
library(permuco)
Hasil_anova <- aovperm(Total_Padatan_Terlarut~Konsentrasi_Starter*Lama_Fermentasi, data = Data_Uji_Fisikokimia_R, np= 10000)
summary(Hasil_anova)
library(permuco)
Hasil_anova <- aovperm(Total_Padatan_Terlarut~Konsentrasi_Starter+Lama_Fermentasi, data = Data_Uji_Fisikokimia_R, np= 10000)
summary(Hasil_anova)
library(rcompanion)
res_posthoc_Konsentrasi_Starter <- pairwisePermutationTest(Total_Padatan_Terlarut~Konsentrasi_Starter, data = Data_Uji_Fisikokimia_R, method = "fdr")
print(res_posthoc_Konsentrasi_Starter)
## Comparison Stat p.value p.adjust
## 1 0.05 - 0.1 = 0 0.4025 0.6873 0.6873
## 2 0.05 - 0.15 = 0 1.771 0.07652 0.2296
## 3 0.1 - 0.15 = 0 1.416 0.1569 0.2354
library(rcompanion)
res_posthoc_Lama_Fermentasi <- pairwisePermutationTest(Total_Padatan_Terlarut~Lama_Fermentasi, data = Data_Uji_Fisikokimia_R, method = "fdr")
print(res_posthoc_Lama_Fermentasi)
## Comparison Stat p.value p.adjust
## 1 18 Jam - 24 Jam = 0 2.566 0.01027 0.0154
## 2 18 Jam - 36 Jam = 0 2.793 0.00522 0.0154
## 3 24 Jam - 36 Jam = 0 1.43 0.1528 0.1528
library(permuco)
Hasil_anova <- aovperm(Kadar_Protein~Konsentrasi_Starter*Lama_Fermentasi, data= Data_Uji_Fisikokimia_R, np= 10000)
summary(Hasil_anova)
library(permuco)
Hasil_anova <- aovperm(Kadar_Protein~Konsentrasi_Starter+Lama_Fermentasi, data= Data_Uji_Fisikokimia_R, np= 10000)
summary(Hasil_anova)
library(rcompanion)
res_posthoc_Konsentrasi_Starter <- pairwisePermutationTest(Kadar_Protein~Konsentrasi_Starter, data = Data_Uji_Fisikokimia_R, method = "fdr")
print(res_posthoc_Konsentrasi_Starter)
## Comparison Stat p.value p.adjust
## 1 0.05 - 0.1 = 0 2.147 0.03178 0.04767
## 2 0.05 - 0.15 = 0 2.563 0.01037 0.03111
## 3 0.1 - 0.15 = 0 0.8576 0.3911 0.39110
library(permuco)
Hasil_anova <- aovperm(Kadar_Lemak~Konsentrasi_Starter*Lama_Fermentasi, data= Data_Uji_Fisikokimia_R, np= 10000)
summary(Hasil_anova)
library(permuco)
Hasil_anova <- aovperm(Kadar_Lemak~Konsentrasi_Starter+Lama_Fermentasi, data= Data_Uji_Fisikokimia_R, np= 10000)
summary(Hasil_anova)
library(rcompanion)
res_posthoc_Konsentrasi_Starter <- pairwisePermutationTest(Kadar_Lemak~Konsentrasi_Starter, data = Data_Uji_Fisikokimia_R, method = "fdr")
print(res_posthoc_Konsentrasi_Starter)
## Comparison Stat p.value p.adjust
## 1 0.05 - 0.1 = 0 -2.5 0.01241 0.018620
## 2 0.05 - 0.15 = 0 -2.948 0.003195 0.009585
## 3 0.1 - 0.15 = 0 -1.682 0.09266 0.092660
library(permuco)
Hasil_anova <- aovperm(Kadar_Abu~Konsentrasi_Starter*Lama_Fermentasi, Data_Uji_Fisikokimia_R, np= 10000)
summary(Hasil_anova)
library(permuco)
Hasil_anova <- aovperm(Kadar_Abu~Konsentrasi_Starter+Lama_Fermentasi, data= Data_Uji_Fisikokimia_R, np= 10000)
summary(Hasil_anova)
library(permuco)
Hasil_anova <- aovperm(Total_Gula~Konsentrasi_Starter*Lama_Fermentasi, data= Data_Uji_Fisikokimia_R, np= 10000)
summary(Hasil_anova)
library(permuco)
Hasil_anova <- aovperm(Total_Gula~Konsentrasi_Starter+Lama_Fermentasi, data= Data_Uji_Fisikokimia_R, np= 10000)
summary(Hasil_anova)
library(rcompanion)
res_posthoc_Konsentrasi_Starter <- pairwisePermutationTest(Total_Gula~Konsentrasi_Starter, data = Data_Uji_Fisikokimia_R, method = "fdr")
print(res_posthoc_Konsentrasi_Starter)
## Comparison Stat p.value p.adjust
## 1 0.05 - 0.1 = 0 0.9358 0.3494 0.3494
## 2 0.05 - 0.15 = 0 1.892 0.05847 0.1754
## 3 0.1 - 0.15 = 0 1.373 0.1696 0.2544
library(rcompanion)
res_posthoc_Lama_Fermentasi <- pairwisePermutationTest(Total_Gula~Lama_Fermentasi, data = Data_Uji_Fisikokimia_R, method = "fdr")
print(res_posthoc_Lama_Fermentasi)
## Comparison Stat p.value p.adjust
## 1 18 Jam - 24 Jam = 0 0.1985 0.8427 0.84270
## 2 18 Jam - 36 Jam = 0 2.683 0.007288 0.01093
## 3 24 Jam - 36 Jam = 0 2.703 0.006863 0.01093
library(permuco)
Hasil_anova <- aovperm(Kadar_Karbohidrat~Konsentrasi_Starter*Lama_Fermentasi, data= Data_Uji_Fisikokimia_R, np= 10000)
summary(Hasil_anova)
library(permuco)
Hasil_anova <- aovperm(Kadar_Karbohidrat~Konsentrasi_Starter+Lama_Fermentasi, data= Data_Uji_Fisikokimia_R, np= 10000)
summary(Hasil_anova)
library(rcompanion)
res_posthoc_Konsentrasi_Starter <- pairwisePermutationTest(Kadar_Karbohidrat~Konsentrasi_Starter, data = Data_Uji_Fisikokimia_R, method = "fdr")
print(res_posthoc_Konsentrasi_Starter)
## Comparison Stat p.value p.adjust
## 1 0.05 - 0.1 = 0 0.9368 0.3488 0.3488
## 2 0.05 - 0.15 = 0 1.891 0.05864 0.1759
## 3 0.1 - 0.15 = 0 1.372 0.1701 0.2552
library(rcompanion)
res_posthoc_Lama_Fermentasi <- pairwisePermutationTest(Kadar_Karbohidrat~Lama_Fermentasi, data = Data_Uji_Fisikokimia_R, method = "fdr")
print(res_posthoc_Lama_Fermentasi)
## Comparison Stat p.value p.adjust
## 1 18 Jam - 24 Jam = 0 0.2009 0.8408 0.84080
## 2 18 Jam - 36 Jam = 0 2.686 0.00723 0.01084
## 3 24 Jam - 36 Jam = 0 2.703 0.006873 0.01084
library(readxl)
Analisis_Data_Viskositas_dan_Kadar_Alkohol_R<- read_excel("D:/SKRIPSI ANGGUN/Analisis Data Viskositas dan Kadar Alkohol R.xlsx")
library(permuco)
Hasil_anova <- aovperm(Viskositas_Kefir~Konsentrasi_Starter*Lama_Fermentasi, data= Analisis_Data_Viskositas_dan_Kadar_Alkohol_R, np= 10000)
## Warning in Pmat(np = np, n = length(y), type = type): n!<= np 'all'
## permutations are feasible, Pmat is computed with the 'all' counting.
## Warning in aovperm_fix(formula = formula, data = data, method = method, : The
## number of permutations is below 2000, p-values might be unreliable.
## Warning in check_distribution(distribution = distribution, digits = 10, : the
## distribution of Konsentrasi_Starter, Lama_Fermentasi,
## Konsentrasi_Starter:Lama_Fermentasi may be discrete.
summary(Hasil_anova)
library(permuco)
Hasil_anova <- aovperm(Viskositas_Kefir~Konsentrasi_Starter+Lama_Fermentasi, data= Analisis_Data_Viskositas_dan_Kadar_Alkohol_R, np= 10000)
## Warning in Pmat(np = np, n = length(y), type = type): n!<= np 'all'
## permutations are feasible, Pmat is computed with the 'all' counting.
## Warning in aovperm_fix(formula = formula, data = data, method = method, : The
## number of permutations is below 2000, p-values might be unreliable.
## Warning in check_distribution(distribution = distribution, digits = 10, : the
## distribution of Konsentrasi_Starter, Lama_Fermentasi may be discrete.
summary(Hasil_anova)
library(permuco)
Hasil_anova <- aovperm(Kadar_Alkohol~Konsentrasi_Starter*Lama_Fermentasi, data= Analisis_Data_Viskositas_dan_Kadar_Alkohol_R, np= 10000)
## Warning in Pmat(np = np, n = length(y), type = type): n!<= np 'all'
## permutations are feasible, Pmat is computed with the 'all' counting.
## Warning in aovperm_fix(formula = formula, data = data, method = method, : The
## number of permutations is below 2000, p-values might be unreliable.
## Warning in check_distribution(distribution = distribution, digits = 10, : the
## distribution of Konsentrasi_Starter, Lama_Fermentasi,
## Konsentrasi_Starter:Lama_Fermentasi may be discrete.
summary(Hasil_anova)
library(permuco)
Hasil_anova <- aovperm(Kadar_Alkohol~Konsentrasi_Starter+Lama_Fermentasi, data= Analisis_Data_Viskositas_dan_Kadar_Alkohol_R, np= 10000)
## Warning in Pmat(np = np, n = length(y), type = type): n!<= np 'all'
## permutations are feasible, Pmat is computed with the 'all' counting.
## Warning in aovperm_fix(formula = formula, data = data, method = method, : The
## number of permutations is below 2000, p-values might be unreliable.
## Warning in check_distribution(distribution = distribution, digits = 10, : the
## distribution of Konsentrasi_Starter, Lama_Fermentasi may be discrete.
summary(Hasil_anova)
library(rcompanion)
res_posthoc_Konsentrasi_Starter <- pairwisePermutationTest(Kadar_Alkohol~Konsentrasi_Starter, data = Analisis_Data_Viskositas_dan_Kadar_Alkohol_R, method = "fdr")
print(res_posthoc_Konsentrasi_Starter)
## Comparison Stat p.value p.adjust
## 1 0.05 - 0.1 = 0 -2.184 0.02898 0.02898
library(rcompanion)
res_posthoc_Lama_Fermentasi <- pairwisePermutationTest(Kadar_Alkohol~Lama_Fermentasi, data = Analisis_Data_Viskositas_dan_Kadar_Alkohol_R, method = "fdr")
print(res_posthoc_Lama_Fermentasi)
## Comparison Stat p.value p.adjust
## 1 18 Jam - 24 Jam = 0 -1.508 0.1315 0.1315
tinytex::tinytex_root("C:/Users/ASUS/Downloads/TinyTeX.zip")
## [1] "C:\\Users\\ASUS\\AppData\\Roaming\\TinyTeX"
tinytex::is_tinytex()
## [1] TRUE