#install.packages("tidyverse")
#install.packages("ggpubr")
#install.packages("readxl")
#install.packages("sp")
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)
library(dplyr)
library(sp)
#import file excel
padi <- readxl::read_excel("soal 2 split plot.xlsx")
head(padi,10)
## # A tibble: 10 x 4
## Pupuk Genotipe Kelompok Hasil_Padi
## <chr> <chr> <dbl> <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
#mengubah setiap faKtor dan ulangan ke dalam bentuk factor
padi <- padi %>% mutate_if(is.character,as.factor) %>% mutate(Kelompok=as.factor(Kelompok))
#Anova
anova_padi <- with(padi,sp.plot(block = Kelompok,
pplot = Pupuk,
splot = Genotipe,
Y = Hasil_Padi))
##
## ANALYSIS SPLIT PLOT: Hasil_Padi
## Class level information
##
## Pupuk : Kontrol PK N NP NK NPK
## Genotipe : IR-64 5-969
## Kelompok : 1 2 3 4
##
## Number of observations: 48
##
## Analysis of Variance Table
##
## Response: Hasil_Padi
## Df Sum Sq Mean Sq F value Pr(>F)
## Kelompok 3 197.11 65.70 3.6812 0.036212 *
## Pupuk 5 1674.80 334.96 18.7668 5.616e-06 ***
## Ea 15 267.73 17.85
## Genotipe 1 0.04 0.04 0.0114 0.916217
## Pupuk:Genotipe 5 78.59 15.72 5.0814 0.004444 **
## Eb 18 55.68 3.09
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## cv(a) = 10.6 %, cv(b) = 4.4 %, Mean = 39.71458