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##  Min.   : 4.0   Min.   :  2.00  
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##  Median :15.0   Median : 36.00  
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Rafi Ganteng

##Kode Baru Kode baru: italic code bold

Struktur Data & Pembersihan

data_mobil <- mtcars

data_mobil$am <- factor(data_mobil$am,
                        levels = c(0,1),
                        labels = c("Automatic","Manual"))

laporan_objek <- list(
  nama_mobil = rownames(mtcars),
  data_frame = data_mobil,
  matriks_5_baris = as.matrix(head(data_mobil, 5))
)

laporan_objek
## $nama_mobil
##  [1] "Mazda RX4"           "Mazda RX4 Wag"       "Datsun 710"         
##  [4] "Hornet 4 Drive"      "Hornet Sportabout"   "Valiant"            
##  [7] "Duster 360"          "Merc 240D"           "Merc 230"           
## [10] "Merc 280"            "Merc 280C"           "Merc 450SE"         
## [13] "Merc 450SL"          "Merc 450SLC"         "Cadillac Fleetwood" 
## [16] "Lincoln Continental" "Chrysler Imperial"   "Fiat 128"           
## [19] "Honda Civic"         "Toyota Corolla"      "Toyota Corona"      
## [22] "Dodge Challenger"    "AMC Javelin"         "Camaro Z28"         
## [25] "Pontiac Firebird"    "Fiat X1-9"           "Porsche 914-2"      
## [28] "Lotus Europa"        "Ford Pantera L"      "Ferrari Dino"       
## [31] "Maserati Bora"       "Volvo 142E"         
## 
## $data_frame
##                      mpg cyl  disp  hp drat    wt  qsec vs        am gear carb
## Mazda RX4           21.0   6 160.0 110 3.90 2.620 16.46  0    Manual    4    4
## Mazda RX4 Wag       21.0   6 160.0 110 3.90 2.875 17.02  0    Manual    4    4
## Datsun 710          22.8   4 108.0  93 3.85 2.320 18.61  1    Manual    4    1
## Hornet 4 Drive      21.4   6 258.0 110 3.08 3.215 19.44  1 Automatic    3    1
## Hornet Sportabout   18.7   8 360.0 175 3.15 3.440 17.02  0 Automatic    3    2
## Valiant             18.1   6 225.0 105 2.76 3.460 20.22  1 Automatic    3    1
## Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0 Automatic    3    4
## Merc 240D           24.4   4 146.7  62 3.69 3.190 20.00  1 Automatic    4    2
## Merc 230            22.8   4 140.8  95 3.92 3.150 22.90  1 Automatic    4    2
## Merc 280            19.2   6 167.6 123 3.92 3.440 18.30  1 Automatic    4    4
## Merc 280C           17.8   6 167.6 123 3.92 3.440 18.90  1 Automatic    4    4
## Merc 450SE          16.4   8 275.8 180 3.07 4.070 17.40  0 Automatic    3    3
## Merc 450SL          17.3   8 275.8 180 3.07 3.730 17.60  0 Automatic    3    3
## Merc 450SLC         15.2   8 275.8 180 3.07 3.780 18.00  0 Automatic    3    3
## Cadillac Fleetwood  10.4   8 472.0 205 2.93 5.250 17.98  0 Automatic    3    4
## Lincoln Continental 10.4   8 460.0 215 3.00 5.424 17.82  0 Automatic    3    4
## Chrysler Imperial   14.7   8 440.0 230 3.23 5.345 17.42  0 Automatic    3    4
## Fiat 128            32.4   4  78.7  66 4.08 2.200 19.47  1    Manual    4    1
## Honda Civic         30.4   4  75.7  52 4.93 1.615 18.52  1    Manual    4    2
## Toyota Corolla      33.9   4  71.1  65 4.22 1.835 19.90  1    Manual    4    1
## Toyota Corona       21.5   4 120.1  97 3.70 2.465 20.01  1 Automatic    3    1
## Dodge Challenger    15.5   8 318.0 150 2.76 3.520 16.87  0 Automatic    3    2
## AMC Javelin         15.2   8 304.0 150 3.15 3.435 17.30  0 Automatic    3    2
## Camaro Z28          13.3   8 350.0 245 3.73 3.840 15.41  0 Automatic    3    4
## Pontiac Firebird    19.2   8 400.0 175 3.08 3.845 17.05  0 Automatic    3    2
## Fiat X1-9           27.3   4  79.0  66 4.08 1.935 18.90  1    Manual    4    1
## Porsche 914-2       26.0   4 120.3  91 4.43 2.140 16.70  0    Manual    5    2
## Lotus Europa        30.4   4  95.1 113 3.77 1.513 16.90  1    Manual    5    2
## Ford Pantera L      15.8   8 351.0 264 4.22 3.170 14.50  0    Manual    5    4
## Ferrari Dino        19.7   6 145.0 175 3.62 2.770 15.50  0    Manual    5    6
## Maserati Bora       15.0   8 301.0 335 3.54 3.570 14.60  0    Manual    5    8
## Volvo 142E          21.4   4 121.0 109 4.11 2.780 18.60  1    Manual    4    2
## 
## $matriks_5_baris
##                   mpg    cyl disp  hp    drat   wt      qsec    vs  am         
## Mazda RX4         "21.0" "6" "160" "110" "3.90" "2.620" "16.46" "0" "Manual"   
## Mazda RX4 Wag     "21.0" "6" "160" "110" "3.90" "2.875" "17.02" "0" "Manual"   
## Datsun 710        "22.8" "4" "108" " 93" "3.85" "2.320" "18.61" "1" "Manual"   
## Hornet 4 Drive    "21.4" "6" "258" "110" "3.08" "3.215" "19.44" "1" "Automatic"
## Hornet Sportabout "18.7" "8" "360" "175" "3.15" "3.440" "17.02" "0" "Automatic"
##                   gear carb
## Mazda RX4         "4"  "4" 
## Mazda RX4 Wag     "4"  "4" 
## Datsun 710        "4"  "1" 
## Hornet 4 Drive    "3"  "1" 
## Hornet Sportabout "3"  "2"

Conditional & Loop

data_mobil$efisiensi <- ifelse(data_mobil$mpg > 20, "Irit", "Boros")

data_mobil[, c("mpg","efisiensi")]
##                      mpg efisiensi
## Mazda RX4           21.0      Irit
## Mazda RX4 Wag       21.0      Irit
## Datsun 710          22.8      Irit
## Hornet 4 Drive      21.4      Irit
## Hornet Sportabout   18.7     Boros
## Valiant             18.1     Boros
## Duster 360          14.3     Boros
## Merc 240D           24.4      Irit
## Merc 230            22.8      Irit
## Merc 280            19.2     Boros
## Merc 280C           17.8     Boros
## Merc 450SE          16.4     Boros
## Merc 450SL          17.3     Boros
## Merc 450SLC         15.2     Boros
## Cadillac Fleetwood  10.4     Boros
## Lincoln Continental 10.4     Boros
## Chrysler Imperial   14.7     Boros
## Fiat 128            32.4      Irit
## Honda Civic         30.4      Irit
## Toyota Corolla      33.9      Irit
## Toyota Corona       21.5      Irit
## Dodge Challenger    15.5     Boros
## AMC Javelin         15.2     Boros
## Camaro Z28          13.3     Boros
## Pontiac Firebird    19.2     Boros
## Fiat X1-9           27.3      Irit
## Porsche 914-2       26.0      Irit
## Lotus Europa        30.4      Irit
## Ford Pantera L      15.8     Boros
## Ferrari Dino        19.7     Boros
## Maserati Bora       15.0     Boros
## Volvo 142E          21.4      Irit
i <- 1
while (i <= nrow(data_mobil)) {
  if (data_mobil$hp[i] > 200) {
    cat("Mobil dengan hp > 200 ditemukan:", rownames(data_mobil)[i], "\n")
    break
  }
  i <- i + 1
}
## Mobil dengan hp > 200 ditemukan: Duster 360