Projek

Daftar Library

library(readxl)
library(olsrr)

## Warning: package 'olsrr' was built under R version 4.4.2

## 
## Attaching package: 'olsrr'

## The following object is masked from 'package:datasets':
## 
##     rivers

library(lmtest)

## Warning: package 'lmtest' was built under R version 4.4.2

## Loading required package: zoo

## Warning: package 'zoo' was built under R version 4.4.2

## 
## Attaching package: 'zoo'

## The following objects are masked from 'package:base':
## 
##     as.Date, as.Date.numeric

library (car)

## Loading required package: carData

Input Data

data<-read_xlsx("D:/R SEI/projek.xlsx")
data

## # A tibble: 11 × 5
##    Tahun Pertumbuhan_Ekonomi  Ekspor Penerimaan_Perpajakan Tingkat_Pengangguran
##    <dbl>               <dbl>   <dbl>                 <dbl>                <dbl>
##  1  2013            9546134  182552.              1077307.                 6.17
##  2  2014           10565817. 175980               1146866.                 5.94
##  3  2015           11540790. 150366.              1240419.                 6.18
##  4  2016           12401728. 145134               1284970.                 5.61
##  5  2017           13589826  168828.              1343530.                 5.5 
##  6  2018           14838756  180013.              1518790.                 5.3 
##  7  2019           15832657. 167683               1546142.                 5.23
##  8  2020           15443353. 163192.              1285136.                 7.07
##  9  2021           16976751. 231610.              1547841.                 6.49
## 10  2022           19588090. 291904.              2034552.                 5.86
## 11  2023           20892377. 258774.              2118348                  5.32

Model Regresi Linear Berganda

model<- lm(Pertumbuhan_Ekonomi ~ Ekspor + Penerimaan_Perpajakan + Tingkat_Pengangguran, data = data)
summary (model)

## 
## Call:
## lm(formula = Pertumbuhan_Ekonomi ~ Ekspor + Penerimaan_Perpajakan + 
##     Tingkat_Pengangguran, data = data)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -1518941  -341078   -36772   516991  1043526 
## 
## Coefficients:
##                         Estimate Std. Error t value Pr(>|t|)    
## (Intercept)           -1.242e+07  4.132e+06  -3.005 0.019805 *  
## Ekspor                -2.600e+01  1.249e+01  -2.081 0.075975 .  
## Penerimaan_Perpajakan  1.432e+01  1.877e+00   7.631 0.000123 ***
## Tingkat_Pengangguran   1.880e+06  5.958e+05   3.156 0.016017 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 870900 on 7 degrees of freedom
## Multiple R-squared:  0.959,  Adjusted R-squared:  0.9414 
## F-statistic: 54.54 on 3 and 7 DF,  p-value: 3.204e-05

Normalitas

ks.test(model$residual, ecdf(model$residual))

## 
##  Exact one-sample Kolmogorov-Smirnov test
## 
## data:  model$residual
## D = 0.090909, p-value = 0.9999
## alternative hypothesis: two-sided

Homoskedastisitas

bptest(model)

## 
##  studentized Breusch-Pagan test
## 
## data:  model
## BP = 1.1631, df = 3, p-value = 0.7619

Multikolinearitas

ols_vif_tol(model)

##               Variables Tolerance      VIF
## 1                Ekspor 0.2170342 4.607569
## 2 Penerimaan_Perpajakan 0.1874068 5.335986
## 3  Tingkat_Pengangguran 0.6562076 1.523908

Autokorelasi

bgtest(model)

## 
##  Breusch-Godfrey test for serial correlation of order up to 1
## 
## data:  model
## LM test = 0.43407, df = 1, p-value = 0.51