NurArfah_PutriRamadhani.R

library(readxl)

## Warning: package 'readxl' was built under R version 4.3.3

tugas_komstat <- read_excel("Semester 4/komputasi statistik/tugas_komstat.xlsx")
View(tugas_komstat)
#split data by colomns
data1 <- tugas_komstat[,c ("X1","Y")]
data1 <- na.omit(data1)
data1

## # A tibble: 5 × 2
##      X1     Y
##   <dbl> <dbl>
## 1 74     8.25
## 2 69     8.53
## 3  6.81 10.7 
## 4  1.05 10.8 
## 5  1.36  8.89

data2 <- tugas_komstat[,c("X2","Y")]
data2 <- na.omit(data2)
data2

## # A tibble: 5 × 2
##      X2     Y
##   <dbl> <dbl>
## 1  5.92  8.25
## 2  5.93  8.53
## 3  1.98 10.7 
## 4  2.62 10.8 
## 5  4.71  8.89

library(ggplot2)

## Warning: package 'ggplot2' was built under R version 4.3.3

ggplot(data1, aes(data1$X1, data1$Y)) + geom_point() + ggtitle("Plot Data 1") + xlab ("X1") + ylab("Y")

## Warning: Use of `data1$X1` is discouraged.
## ℹ Use `X1` instead.

## Warning: Use of `data1$Y` is discouraged.
## ℹ Use `Y` instead.

ggplot(data2, aes(data2$X2, data2$Y)) + geom_point() + ggtitle("Plot Data 2") + xlab ("X2") + ylab("Y")

## Warning: Use of `data2$X2` is discouraged.
## ℹ Use `X2` instead.

## Warning: Use of `data2$Y` is discouraged.
## ℹ Use `Y` instead.

#nilai korelasi
cor(data1$X1, data1$Y)

## [1] -0.7634441

cor(data2$X2, data2$Y)

## [1] -0.9807313

#korelasi
model1 <- lm (Y~ X1, data = data1)
model1

## 
## Call:
## lm(formula = Y ~ X1, data = data1)
## 
## Coefficients:
## (Intercept)           X1  
##    10.20840     -0.02511

model2 <- lm (Y~ X2, data = data2)
model2

## 
## Call:
## lm(formula = Y ~ X2, data = data2)
## 
## Coefficients:
## (Intercept)           X2  
##     12.2236      -0.6568

ggplot(data1, aes(data1$X1, data1$Y)) + geom_point() + ggtitle("Plot Data 1") + xlab ("X1") + ylab("Y") + geom_smooth(method = "lm", se = FALSE)

## Warning: Use of `data1$X1` is discouraged.
## ℹ Use `X1` instead.

## Warning: Use of `data1$Y` is discouraged.
## ℹ Use `Y` instead.

## Warning: Use of `data1$X1` is discouraged.
## ℹ Use `X1` instead.

## Warning: Use of `data1$Y` is discouraged.
## ℹ Use `Y` instead.

## `geom_smooth()` using formula = 'y ~ x'

ggplot(data2, aes(data2$X2, data2$Y)) + geom_point() + ggtitle("Plot Data 2") + xlab ("X2") + ylab("Y") + geom_smooth(method = "lm", se = FALSE)

## Warning: Use of `data2$X2` is discouraged.
## ℹ Use `X2` instead.

## Warning: Use of `data2$Y` is discouraged.
## ℹ Use `Y` instead.

## Warning: Use of `data2$X2` is discouraged.
## ℹ Use `X2` instead.

## Warning: Use of `data2$Y` is discouraged.
## ℹ Use `Y` instead.

## `geom_smooth()` using formula = 'y ~ x'

#prediksi
data_baru1 <- data.frame (X1=c(74,69,6,81,1.05,1.36))
hasil_prediksi1 <- predict(model1, data_baru1)
hasil_prediksi1

##         1         2         3         4         5         6 
##  8.350385  8.475927 10.057746  8.174628 10.182032 10.174248

data_baru2 <- data.frame (X2=c(5.92,5.93,1.98,2.62,4.71))
hasil_prediksi2 <- predict(model2, data_baru2)
hasil_prediksi2

##         1         2         3         4         5 
##  8.335328  8.328760 10.923105 10.502755  9.130051