ANALISIS DATA JUMLAH AHLI GIZI DALAM BOX PLOT DAN DOT PLOT #KELOMPOK 5

PROSES IMPORT DATA

#Import Data

library(readxl)
library(formattable)
## Warning: package 'formattable' was built under R version 4.3.3
DATA_KELOMPOK5_KOMSTAT <- read_excel("D:/SEM 3 TUGAS/KOMSTAT/DATA/DATA_KELOMPOK5_KOMSTAT.xls")
View(DATA_KELOMPOK5_KOMSTAT)
formattable(DATA_KELOMPOK5_KOMSTAT)
No Kabupaten/Kota Jumlah Ahli Gizi (Nutritionist)
1 Pacitan 69
2 Ponorogo 58
3 Trenggalek 73
4 Tulungagung 79
5 Blitar 73
6 Kediri 114
7 Malang 118
8 Lumajang 85
9 Jember 106
10 Banyuwangi 99
11 Bondowoso 64
12 Situbondo 61
13 Probolinggo 57
14 Pasuruan 70
15 Sidoarjo 117
16 Mojokerto 54
17 Jombang 89
18 Nganjuk 53
19 Madiun 49
20 Magetan 38
21 Ngawi 63
22 Bojonegoro 67
23 Tuban 56
24 Lamongan 67
25 Gresik 54
26 Bangkalan 32
27 Sampang 40
28 Pamekasan 46
29 Sumenep 48
30 Kediri 58
31 Blitar 29
32 Malang 168
33 Probolinggo 30
34 Pasuruan 24
35 Mojokerto 31
36 Madiun 57
37 Surabaya 310
38 Batu 27

PENGECEKAN LOKASI SINTAKS

Langkah awal adalah pengecekan di mana lokasi sintaks ini disimpan

getwd()
## [1] "C:/Users/padhl/AppData/Local/Microsoft/Windows/INetCache/IE/271NOX2X"

#Mean

Mean<-mean(DATA_KELOMPOK5_KOMSTAT$`Jumlah Ahli Gizi (Nutritionist)`)
Mean
## [1] 71.92105

#Median

Median<-median(DATA_KELOMPOK5_KOMSTAT$`Jumlah Ahli Gizi (Nutritionist)`)
Median
## [1] 59.5

Range

NilaiMax<-max(DATA_KELOMPOK5_KOMSTAT$`Jumlah Ahli Gizi (Nutritionist)`)
NilaiMax
## [1] 310
NilaiMin<-min(DATA_KELOMPOK5_KOMSTAT$`Jumlah Ahli Gizi (Nutritionist)`)
NilaiMin
## [1] 24
rangedata<-NilaiMax-NilaiMin
rangedata
## [1] 286

###Kuartil 1

Q1<-quantile(DATA_KELOMPOK5_KOMSTAT$`Jumlah Ahli Gizi (Nutritionist)`, probs=(0.25))
Q1
##   25% 
## 48.25

###Kuartil 3

Q3<-quantile(DATA_KELOMPOK5_KOMSTAT$`Jumlah Ahli Gizi (Nutritionist)`, probs=(0.75))
Q3
##  75% 
## 77.5

###IQR

IQR <- Q3-Q1
IQR
##   75% 
## 29.25

###STDEV

STDEV<-sd(DATA_KELOMPOK5_KOMSTAT$`Jumlah Ahli Gizi (Nutritionist)`)
STDEV
## [1] 49.80469

VARIANS

Varian<-var(DATA_KELOMPOK5_KOMSTAT$`Jumlah Ahli Gizi (Nutritionist)`)
Varian
## [1] 2480.507

#Grafik Box-Plot #Hinges

H1<-Q1
H1
##   25% 
## 48.25
H2<-Q3
H2
##  75% 
## 77.5

#Nilai Ekstrem

NilaiEkstrem <- (DATA_KELOMPOK5_KOMSTAT$`Jumlah Ahli Gizi (Nutritionist)` > Q3+3*IQR) | 
  (DATA_KELOMPOK5_KOMSTAT$`Jumlah Ahli Gizi (Nutritionist)` < Q1-3*IQR)
a<-Q3+3*IQR
a
##    75% 
## 165.25
b<-Q1-3*IQR
b
##   25% 
## -39.5

#Nilai Ekstrem

DATA_KELOMPOK5_KOMSTAT$`Jumlah Ahli Gizi (Nutritionist)`[(NilaiEkstrem)]
## [1] 168 310

#Outlier

Outlier <- (DATA_KELOMPOK5_KOMSTAT$`Jumlah Ahli Gizi (Nutritionist)` > Q3+1.5*IQR) | 
  (DATA_KELOMPOK5_KOMSTAT$`Jumlah Ahli Gizi (Nutritionist)` < Q1-1.5*IQR)
p<-Q3+1.5*IQR
p
##     75% 
## 121.375
q<-Q1-1.5*IQR
q
##   25% 
## 4.375

#Membuat Box Plot

boxplot(DATA_KELOMPOK5_KOMSTAT$`Jumlah Ahli Gizi (Nutritionist)`, horizontal =F ,
        main = "Box Plot Jumlah Ahli Gizi (Nutritionist) ", col="#FA8072", 
        border = "#008000",pch=19,
        ylab="Jumlah Ahli Gizi (Nutritionist)")

#Membuat Dot Plot

library(ggplot2)
## Warning: package 'ggplot2' was built under R version 4.3.3
ggplot(DATA_KELOMPOK5_KOMSTAT, aes(x = DATA_KELOMPOK5_KOMSTAT$`Jumlah Ahli Gizi (Nutritionist)`)) +
  geom_dotplot(fill = "#FA8072") +
  theme_minimal() +                                 
  labs(title = "Dot Plot Jumlah Ahli Gizi (Nutritionist)",
       y = "Proporsi",
       x = "Jumlah Ahli Gizi (Nutritionist)")
## Warning: Use of `` DATA_KELOMPOK5_KOMSTAT$`Jumlah Ahli Gizi (Nutritionist)` `` is
## discouraged.
## ℹ Use `Jumlah Ahli Gizi (Nutritionist)` instead.
## Bin width defaults to 1/30 of the range of the data. Pick better value with
## `binwidth`.

# UJI NORMALITAS

library(nortest)
ad.test(DATA_KELOMPOK5_KOMSTAT$`Jumlah Ahli Gizi (Nutritionist)`)
## 
##  Anderson-Darling normality test
## 
## data:  DATA_KELOMPOK5_KOMSTAT$`Jumlah Ahli Gizi (Nutritionist)`
## A = 2.9409, p-value = 1.541e-07

#Transformasi data

library(rcompanion)
trans1<- transformTukey(DATA_KELOMPOK5_KOMSTAT$`Jumlah Ahli Gizi (Nutritionist)`)

## 
##     lambda     W Shapiro.p.value
## 388 -0.325 0.976          0.5781
## 
## if (lambda >  0){TRANS = x ^ lambda} 
## if (lambda == 0){TRANS = log(x)} 
## if (lambda <  0){TRANS = -1 * x ^ lambda}

trans1
##  [1] -0.2525655 -0.2672304 -0.2479819 -0.2416970 -0.2479819 -0.2145388
##  [7] -0.2121477 -0.2360146 -0.2196725 -0.2246046 -0.2588162 -0.2628862
## [13] -0.2687452 -0.2513872 -0.2127353 -0.2735093 -0.2325135 -0.2751759
## [19] -0.2822840 -0.3065987 -0.2601443 -0.2549915 -0.2702955 -0.2549915
## [25] -0.2735093 -0.3242099 -0.3015300 -0.2881401 -0.2841820 -0.2672304
## [31] -0.3347501 -0.1891361 -0.3310820 -0.3559847 -0.3275725 -0.2687452
## [37] -0.1549913 -0.3426153

ANDERSON DARLING SETELAH TRANSFORMASI PERTAMA

ad.test(trans1)
## 
##  Anderson-Darling normality test
## 
## data:  trans1
## A = 0.42818, p-value = 0.296

Boxplot Seteleh Transformasi Pertama

boxplot(trans1, horizontal =F ,
        main = "Box Plot Jumlah Ahli Gizi (Nutritionist) ", col="#FA8072", 
        border = "#008000",pch=19,
        ylab="Jumlah Ahli Gizi (Nutritionist)")

#VISUALISASI DATA # BARCHART

# Bar chart
barplot(DATA_KELOMPOK5_KOMSTAT$`Jumlah Ahli Gizi (Nutritionist)`, names.arg = DATA_KELOMPOK5_KOMSTAT$`Kabupaten/Kota`, col = "lightgreen", 
        xlab = "Kabupaten/Kota", ylab = "Jumlah Ahli Gizi", 
        main = "Bar Chart Jumlah Ahli Gizi per Kabupaten/Kota", las=2, cex.names=0.7)

# Menambahkan grid pada sumbu y
grid(nx = NA, ny = NULL, col = "gray", lty = "dotted")