#install.packages("tidyverse")
#install.packages("ggpubr")
#install.packages("readxl")
library(tidyverse)
## -- Attaching packages --------------------------------------- tidyverse 1.3.0 --
## v ggplot2 3.3.2 v purrr 0.3.4
## v tibble 3.0.4 v dplyr 1.0.2
## v tidyr 1.1.2 v stringr 1.4.0
## v readr 1.4.0 v forcats 0.5.0
## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
library(readxl)
library(agricolae)
library(ggpubr)
#import file excel
padi <- readxl::read_excel("soal 3 split blok.xlsx")
#mengubah setiap faKtor dan ulangan ke dalam bentuk factor
padi <- padi %>% mutate_if(is.character,as.factor) %>% mutate(Ulangan=as.factor(Ulangan))
head(padi,10)
## # A tibble: 10 x 4
## Pupuk Genotipe Ulangan Hasil_Padi
## <fct> <fct> <fct> <dbl>
## 1 Kontrol IR-64 1 20.7
## 2 Kontrol IR-64 2 32.1
## 3 Kontrol IR-64 3 29.5
## 4 Kontrol IR-64 4 37.7
## 5 Kontrol 5-969 1 27.7
## 6 Kontrol 5-969 2 33
## 7 Kontrol 5-969 3 26.3
## 8 Kontrol 5-969 4 37.7
## 9 PK IR-64 1 30
## 10 PK IR-64 2 30.7
#Anova
anova_padi <- with(padi,strip.plot(BLOCK = Ulangan,
COL = Pupuk,ROW = Genotipe,
Y = Hasil_Padi )
)
##
## ANALYSIS STRIP PLOT: Hasil_Padi
## Class level information
##
## Pupuk : Kontrol PK N NP NK NPK
## Genotipe : IR-64 5-969
## Ulangan : 1 2 3 4
##
## Number of observations: 48
##
## model Y: Hasil_Padi ~ Ulangan + Pupuk + Ea + Genotipe + Eb + Genotipe:Pupuk + Ec
##
## Analysis of Variance Table
##
## Response: Hasil_Padi
## Df Sum Sq Mean Sq F value Pr(>F)
## Ulangan 3 197.11 65.70 18.8263 2.402e-05 ***
## Pupuk 5 1674.80 334.96 18.7668 5.616e-06 ***
## Ea 15 267.73 17.85 5.1142 0.001537 **
## Genotipe 1 0.04 0.04 0.0317 0.869973
## Eb 3 3.33 1.11 0.3180 0.812236
## Genotipe:Pupuk 5 78.59 15.72 4.5038 0.010471 *
## Ec 15 52.35 3.49
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## cv(a) = 10.6 %, cv(b) = 2.7 %, cv(c) = 4.7 %, Mean = 39.71458