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  1. (NILAI 25) Diketahui \(X\) adalah suatu variabel random dengan pdf sebagai berikut \(f_{X}(x) = \frac{x}{4} e^{-x^{2}/8}, x \ge 0\). Instruksi Permasalahan:
## hasil integral 0.999999999986165
## nilai ekspektasi 2.506628274631
## nilai varians 1.7168146928204
  1. (NILAI 25) Diketahui \(X\) suatu variabel random dengan PDF \(f_{X}(x)=\frac{\alpha}{\beta}(\frac{x}{\beta})^{\alpha-1}\exp(-\frac{x}{\beta})^{\alpha}\) dan CDF \(F_{X}(x)=1-\exp(-\frac{x}{\beta})^{\alpha}\). Instruksi Permasalahan:
  1. (NILAI 25) Nilai penurunan/peningkatan dari suatu saham adalah acak antara -1.0 sampai 1.0. Perusahaan Creabiz dengan saham ‘CRBZ’ melakukan simulasi penurunan/peningkatan saham selama 100 hari kedepan. Instruksi Permasalahan:
##   data_index    data_mean data_growth
## 1       <NA>           NA        <NA>
## 2      day 1 -0.003660899    decrease
## 3      day 2  0.069530165    increase
## 4      day 3  0.090267517    increase
## 5      day 4 -0.101214278    decrease
## 6      day 5 -0.006131964    decrease
  1. (NILAI 25) Nilai penurunan/peningkatan dari suatu saham adalah acak antara -1.0 sampai 1.0. Lakukan simulasi pada R:
## exact mean 0
## estimated mean -0.00301733044818975

  1. (SOAL BONUS) Under the system of floating exchange rates, the exchange rate of foreign currencies against the U.S. Dollar is affected by many random factors, leading to the assumption of a normal distribution of small daily fluctuations. It is believed that the exchange rate of the U.S. dollar per EURO in April 2020 had a mean of 1.36 and a standard deviation of 0.03. Find these:
## probability (a) 0.97724986805182
## probability (b) 7.34341075296987e-06
  1. (SOAL BONUS) Create a 5x5 matrix A and a 5x5 matrix B given by:

\[ A = \begin{bmatrix} 1 & 2 & 3 & 4 & 5 \\ 6 & 7 & 8 & 9 & 10 \\ 11 & 12 & 13 & 14 & 15 \\ 16 & 17 & 18 & 19 & 20 \\ 21 & 22 & 23 & 24 & 25 \end{bmatrix} \]

\[ B = \begin{bmatrix} 25 & 24 & 23 & 22 & 21 \\ 20 & 19 & 18 & 17 & 16 \\ 15 & 14 & 13 & 12 & 11 \\ 10 & 9 & 8 & 7 & 6 \\ 5 & 4 & 3 & 2 & 1 \end{bmatrix} \]

## 
##  matriks A
##            [,1]  [,2]      [,3]      [,4]      [,5]
## [1,] 0.06666667 0.150 0.1692308 0.1777778 0.1826087
## [2,] 0.13333333 0.175 0.1846154 0.1888889 0.1913043
## [3,] 0.20000000 0.200 0.2000000 0.2000000 0.2000000
## [4,] 0.26666667 0.225 0.2153846 0.2111111 0.2086957
## [5,] 0.33333333 0.250 0.2307692 0.2222222 0.2173913
## 
##  matriks B
##           [,1]      [,2] [,3]      [,4]       [,5]
## [1,] 0.3333333 0.2666667  0.2 0.1333333 0.06666667
## [2,] 0.3428571 0.2714286  0.2 0.1285714 0.05714286
## [3,] 0.3538462 0.2769231  0.2 0.1230769 0.04615385
## [4,] 0.3666667 0.2833333  0.2 0.1166667 0.03333333
## [5,] 0.3818182 0.2909091  0.2 0.1090909 0.01818182
## 
##  matriks C=A*B
##           [,1]      [,2]      [,3]       [,4]       [,5]
## [1,] 0.2684410 0.2088489 0.1492568 0.08966469 0.03007261
## [2,] 0.3120726 0.2433505 0.1746284 0.10590627 0.03718416
## [3,] 0.3557043 0.2778521 0.2000000 0.12214785 0.04429570
## [4,] 0.3993360 0.3123538 0.2253716 0.13838943 0.05140725
## [5,] 0.4429676 0.3468554 0.2507432 0.15463101 0.05851880
## 
##  eigen C
## eigen() decomposition
## $values
## [1]  9.004130e-01  8.286651e-03  1.382116e-16  4.918299e-17 -1.544146e-17
## 
## $vectors
##            [,1]        [,2]          [,3]       [,4]        [,5]
## [1,] -0.3274847 -0.33592374 -6.324555e-01 -0.2788208 -0.14102127
## [2,] -0.3837777 -0.05943721  6.324555e-01  0.7309009 -0.11987047
## [3,] -0.4400707  0.21704931  3.162278e-01 -0.6073496  0.07113899
## [4,] -0.4963637  0.49353584 -1.812500e-15  0.1372795  0.78141853
## [5,] -0.5526566  0.77002236 -3.162278e-01  0.0179899 -0.59166578