Pendahuluan

Dokumen ini berisi laporan tugas analisis data menggunakan R Markdown. Dataset yang digunakan adalah dataset bawaan dari R, yaitu mtcars, iris, dan airquality. Tujuan dari laporan ini adalah untuk memahami bagaimana data dapat diringkas, divisualisasi, dan dianalisis langsung dalam format dokumen interaktif.

Analisis Dataset mtcars

Dataset mtcars berisi data teknis berbagai mobil.

Menampilkan Beberapa Baris Awal

head(mtcars)
##                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
## Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

Statistik Ringkasan

summary(mtcars)
##       mpg             cyl             disp             hp       
##  Min.   :10.40   Min.   :4.000   Min.   : 71.1   Min.   : 52.0  
##  1st Qu.:15.43   1st Qu.:4.000   1st Qu.:120.8   1st Qu.: 96.5  
##  Median :19.20   Median :6.000   Median :196.3   Median :123.0  
##  Mean   :20.09   Mean   :6.188   Mean   :230.7   Mean   :146.7  
##  3rd Qu.:22.80   3rd Qu.:8.000   3rd Qu.:326.0   3rd Qu.:180.0  
##  Max.   :33.90   Max.   :8.000   Max.   :472.0   Max.   :335.0  
##       drat             wt             qsec             vs        
##  Min.   :2.760   Min.   :1.513   Min.   :14.50   Min.   :0.0000  
##  1st Qu.:3.080   1st Qu.:2.581   1st Qu.:16.89   1st Qu.:0.0000  
##  Median :3.695   Median :3.325   Median :17.71   Median :0.0000  
##  Mean   :3.597   Mean   :3.217   Mean   :17.85   Mean   :0.4375  
##  3rd Qu.:3.920   3rd Qu.:3.610   3rd Qu.:18.90   3rd Qu.:1.0000  
##  Max.   :4.930   Max.   :5.424   Max.   :22.90   Max.   :1.0000  
##        am              gear            carb      
##  Min.   :0.0000   Min.   :3.000   Min.   :1.000  
##  1st Qu.:0.0000   1st Qu.:3.000   1st Qu.:2.000  
##  Median :0.0000   Median :4.000   Median :2.000  
##  Mean   :0.4062   Mean   :3.688   Mean   :2.812  
##  3rd Qu.:1.0000   3rd Qu.:4.000   3rd Qu.:4.000  
##  Max.   :1.0000   Max.   :5.000   Max.   :8.000

Korelasi MPG vs Berat Mobil

cor(mtcars$mpg, mtcars$wt)
## [1] -0.8676594

Visualisasi MPG vs Berat Mobil

plot(mtcars$wt, mtcars$mpg,
     main = "MPG vs Berat Mobil",
     xlab = "Berat (wt)",
     ylab = "MPG",
     col = "blue", pch = 19)

Analisis Dataset iris

Dataset iris berisi data morfologi bunga dari tiga spesies.

Menampilkan Beberapa Data Awal

head(iris)
##   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1          5.1         3.5          1.4         0.2  setosa
## 2          4.9         3.0          1.4         0.2  setosa
## 3          4.7         3.2          1.3         0.2  setosa
## 4          4.6         3.1          1.5         0.2  setosa
## 5          5.0         3.6          1.4         0.2  setosa
## 6          5.4         3.9          1.7         0.4  setosa

Rata-rata Setiap Spesies

aggregate(. ~ Species, data = iris, mean)
##      Species Sepal.Length Sepal.Width Petal.Length Petal.Width
## 1     setosa        5.006       3.428        1.462       0.246
## 2 versicolor        5.936       2.770        4.260       1.326
## 3  virginica        6.588       2.974        5.552       2.026

Visualisasi Sepal Length

boxplot(Sepal.Length ~ Species, data = iris,
        col = c("skyblue", "lightgreen", "pink"),
        main = "Panjang Sepal per Spesies")

Analisis Dataset airquality

Dataset ini berisi kualitas udara harian di New York.

Mengecek Missing Value

sum(is.na(airquality))
## [1] 44

Menghapus Data Kosong dan Ringkasan

airquality_clean <- na.omit(airquality)
summary(airquality_clean)
##      Ozone          Solar.R           Wind            Temp      
##  Min.   :  1.0   Min.   :  7.0   Min.   : 2.30   Min.   :57.00  
##  1st Qu.: 18.0   1st Qu.:113.5   1st Qu.: 7.40   1st Qu.:71.00  
##  Median : 31.0   Median :207.0   Median : 9.70   Median :79.00  
##  Mean   : 42.1   Mean   :184.8   Mean   : 9.94   Mean   :77.79  
##  3rd Qu.: 62.0   3rd Qu.:255.5   3rd Qu.:11.50   3rd Qu.:84.50  
##  Max.   :168.0   Max.   :334.0   Max.   :20.70   Max.   :97.00  
##      Month            Day       
##  Min.   :5.000   Min.   : 1.00  
##  1st Qu.:6.000   1st Qu.: 9.00  
##  Median :7.000   Median :16.00  
##  Mean   :7.216   Mean   :15.95  
##  3rd Qu.:9.000   3rd Qu.:22.50  
##  Max.   :9.000   Max.   :31.00

Visualisasi Ozon vs Temperatur

plot(airquality_clean$Temp, airquality_clean$Ozone,
     main = "Ozon vs Suhu",
     xlab = "Temperatur (F)",
     ylab = "Ozon (ppb)",
     col = "orange", pch = 16)

Kesimpulan

R Markdown memudahkan penulisan laporan analisis karena dapat menggabungkan narasi, kode, dan hasilnya dalam satu dokumen. Dataset mtcars, iris, dan airquality menunjukkan bagaimana data eksploratif dan visualisasi dapat dilakukan dengan cepat.