Tugas 5

Algoritma dan Struktur Data

Email             : garryjuliusperman@gmail.com
rpubs             : https://rpubs.com/Garr
Jurusan          : Statistika Bisnis
Address         : ARA Center, Matana University Tower
                         Jl. CBD Barat Kav, RT.1, Curug Sangereng, Kelapa Dua, Tangerang, Banten 15810.

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1 Integral Tentu dan Tak Tentu

1.1 Integral tentu

masukan=c(1:5)

integral <- function(x)
    {
    x^2 + x-2
    }
    
integral(masukan)

## [1]  0  4 10 18 28

cat("fungsi:",integral(masukan))

## fungsi: 0 4 10 18 28

1.2 Integral tak tentu

library(mosaicCalc)

## Loading required package: mosaicCore

## Registered S3 method overwritten by 'mosaic':
##   method                           from   
##   fortify.SpatialPolygonsDataFrame ggplot2

## 
## Attaching package: 'mosaicCalc'

## The following object is masked from 'package:stats':
## 
##     D

integral = antiD((x + 2)^2 ~x)
integral

## function (x, C = 0) 
## 1/3 * (x + 2)^3 + C

2 Luas Lingkaran, Keliling Lingkaran, dan, Volume Bola.

lingkaran <- function(phi,r)
{
  luas_permukaan = 4*phi*r^2
  keliling = 2*phi*r
  volume = phi*r^2
  return (cat(c("luas permukaan:",luas_permukaan, sep = "/n","keliling:",keliling, sep = "/n", "volume:",volume)))
}
lingkaran(22/7,14)

## luas permukaan: 2464 /n keliling: 88 /n volume: 616

3 Nilai Maksimum, Minimum, Rata-rata, Median, Mode, Variansi, Standard Deviasi pada data berfrekuensi.

nilai <- c(3,2,4,4,1,2.7,2.5,3.25,4,3.6)
frekuensi <- c(2,5,8,15,3,9,13,7,9,3)
data = data.frame(nilai,frekuensi)
data

##    nilai frekuensi
## 1   3.00         2
## 2   2.00         5
## 3   4.00         8
## 4   4.00        15
## 5   1.00         3
## 6   2.70         9
## 7   2.50        13
## 8   3.25         7
## 9   4.00         9
## 10  3.60         3

data = c(rep(3,2),rep(2,5),rep(4,8),rep(4,15),rep(1,3),rep(2.7,9),rep(2.5,13),rep(3.25,7),rep(4,9),rep(3.6,3))
max<-max(data)
min<-min(data)
mean<-mean(data)
median<-median(data)
mode<-mode(data)
variansi<-var(data)
standar_deviasi<-sd(data)

kesimpulan<-c(max,min,mean,median,mode,variansi,standar_deviasi)
names(kesimpulan)<-c(max,min,mean,median,mode,variansi,standar_deviasi)
kesimpulan

##                   4                   1    3.20743243243243                3.25 
##                 "4"                 "1"  "3.20743243243243"              "3.25" 
##             numeric   0.704019344687153    0.83905860622912 
##           "numeric" "0.704019344687153"  "0.83905860622912"