#Simulasi Distribusi Diskrit dan Kontinu ##Buat simulasi untuk distribusi diskrit dan distribusi kontinu. ##1. Distribusi Diskrit ### Sebuah pabrik perakitan komponen elektronik memiliki tingkat kecacatan produk sebesar 10%. Manajer kualitas ingin mensimulasikan jumlah produk cacat jika mereka mengambil sampel sebanyak 50 unit setiap kali pengecekan. Simulasi ini dilakukan sebanyak 500 kali untuk melihat pola distribusi produk cacat dalam jangka panjang. ###n = 50 (jumlah sampel per pengecekan) ###p = 0.15 (probabilitas produk cacat) ###Banyak simulasi = 1000

set.seed(25)
n_sampel <- 50
p_cacat <- 0.1
sim_produksi <- rbinom(500, size = n_sampel, prob = p_cacat)
sim_produksi
##   [1]  4  6  3  8  3 10  6  4  2  4  4  4  9  5  6  3  5  6  5  6  2  5  2  3  4
##  [26]  4  2  5  5  3  7  4  3  2  7  4  8  4  3  3  6  4  5  6  5  4 11  6  2  6
##  [51]  3  6  7  5  5  3  3  5  3  3  3  3  4  6  6  7  5  8  6  3  7  3  2  7  3
##  [76]  5  3  7  3  3  5  4  5  2  7  6  4  4  7  5  5  3  5  6  1  4  6  8  3  3
## [101]  5  4  6  4  2  5  4  5 10  5  3  2  3  3  3  1  8  6  1  3  2  3  5  1  5
## [126]  7  2  7  7  5  2  5  3  7  8  4  5  7  4  5  9 11  3  4  5  5  4  6  8  5
## [151]  4  5  5  4  3  6  5  1  3  9  8  6  4  5  2  7  2  3  5  6  6  3  5  7  4
## [176]  6  3  8  4  3  7  2  9  3  5  5  4  6  2  3  9  0  7  6  4  6  5  1  2  7
## [201]  3  3  2  3  4  7  4  3  7  3  3 13  3  7  5  8  3  4  4  4  6  5  6  8  3
## [226]  9  7  3  4  6  4  3  7  5  8  3  4  7  3  4  6  6  7  6  4  2  5  4  8  4
## [251]  6  5  8  4  4  8  5 10  2  5  3  3  6  5  4  6  3  9  5  8  5  5  7  6  2
## [276]  8  4  5  5  8  6  5  8  6  5 10  3  6  4  5  4  1  5  2  6  2  5  2  2  7
## [301]  4  7  8  7  4  7  5  6  7  9  3  5  3  9  9 15  3  3  3  4  5  6  6  9  4
## [326]  2  4 12  4  3  4  5  4  4  3  4  3  8  5  3  6  4  6  7  3  3  8  5  4  6
## [351]  6  5  4  8 10  8  5  2  4  2  5  4  7  6  3  7  7  5  8  8  6  7  7  8  2
## [376]  7  7  6  3  5 12  5  5  7  7  5  8  6  6  4  3  3  9  4  4  0  1  7  2  4
## [401]  4  6  0  4  4  5  3  7  9  5  6  3  6  6  5  4  4  6  4  5  6  5  2  5  7
## [426]  3  8  9  6  3 10  6  3  7  7  2  6  9  7  6  8  6  6  2  3  1  4  2  3  4
## [451]  6  5  4  8  7  5  5  6  4  6  2  3  4  3  4  4  3  3  4  6  7  7  7  5  7
## [476]  5  5  5  7  0  8  5 11  5  3 11  6  5  7  6  3  7  3  5  6  6  6  3  4  6
mean(sim_produksi)
## [1] 5.016
var(sim_produksi)
## [1] 4.773291
hist(sim_produksi,
     main = "Simulasi Jumlah Produk Cacat",
     xlab = "Jumlah Produk Cacat per 50 Sampel",
     col = "darkseagreen",
     breaks = 30)

###Hasil simulasi menunjukkan bahwa model ini sangat akurat, di mana nilai rata-rata (mean) sebesar 5.016 sangat mendekati nilai teoritisnya yaitu 5, menandakan bahwa dalam setiap batch produksi rata-rata ditemukan sekitar 5 produk cacat. Nilai varians sebesar 4.773 juga menunjukkan penyebaran data yang stabil di sekitar rata-rata dengan fluktuasi yang wajar. Secara visual, grafik histogram di bawah ini mengonfirmasi temuan tersebut dengan puncak frekuensi tertinggi berada di angka 5, yang berarti jumlah 5 cacat adalah kejadian yang paling sering muncul dari 500 kali simulasi yang dilakukan.

##2. Distribusi Kontinu ###Simulasi ini memodelkan berat produk dalam kemasan yang seharusnya memiliki berat standar 500 gram. Dalam proses pengisian otomatis, terdapat variasi kecil yang mengikuti distribusi normal dengan standar deviasi 10 gram. Simulasi dilakukan terhadap 500 unit untuk memantau konsistensi mesin. ### μ = 500 (rata-rata berat ideal) ### σ = 10 (standar deviasi/simpangan baku) ### Banyak simulasi = 500

set.seed(25)
mean_val <- 500
sd_val <- 10
sim_berat <- rnorm(500, mean = mean_val, sd = sd_val)
sim_berat
##   [1] 497.8817 489.5841 488.4669 503.2153 484.9987 495.5447 517.3405 505.1130
##   [9] 500.9965 499.4211 482.5721 486.7505 494.5207 485.4362 500.8269 509.2758
##  [17] 492.8323 509.6240 515.4588 489.9024 505.5741 501.6878 501.5526 523.6776
##  [25] 484.1436 488.9647 509.0279 500.6832 488.5053 490.9873 488.0155 494.8984
##  [33] 503.0625 499.3212 503.7220 511.4449 485.6039 492.5459 489.1574 490.8819
##  [41] 502.5447 500.5454 508.6940 495.0418 507.8898 499.5172 502.8444 476.5509
##  [49] 503.5214 492.6329 501.5287 504.6664 486.5138 496.2867 520.4820 489.6965
##  [57] 491.9109 491.0049 513.2165 480.9741 485.6484 500.4659 499.4981 487.1247
##  [65] 511.5411 486.2426 488.5170 514.1626 501.0576 496.1534 517.8448 488.8471
##  [73] 499.2785 493.4507 512.3475 496.4500 500.2429 488.7985 501.3152 489.8211
##  [81] 515.4413 493.8750 485.2455 486.6116 501.1600 504.4101 502.5333 493.9868
##  [89] 493.1813 493.6159 511.2551 516.8030 499.5418 496.4030 487.2723 516.5151
##  [97] 509.7073 497.0084 500.8634 484.3222 490.6582 482.4902 496.4922 495.0223
## [105] 507.7132 493.0509 492.2371 500.4013 490.3484 495.5644 504.8223 502.9936
## [113] 488.6024 507.5012 496.5395 497.0134 511.5743 513.7832 494.3880 492.7256
## [121] 505.4256 510.7424 493.2849 498.5951 514.6725 505.6336 512.4070 497.4658
## [129] 501.9699 487.0736 492.9976 503.8625 495.1088 491.3688 502.1167 498.9528
## [137] 508.8527 486.6284 495.8026 501.1490 505.7979 513.3755 500.0553 489.5198
## [145] 497.0692 493.9200 502.2270 504.0458 502.1208 487.1629 498.1326 514.7505
## [153] 496.6433 499.2473 509.3825 488.0084 491.7687 517.7585 492.7349 491.4541
## [161] 501.8722 506.6475 496.2134 495.9372 496.2205 494.2172 498.0410 492.4712
## [169] 487.9282 501.0304 507.0757 504.8819 493.2565 514.5780 495.7318 503.7208
## [177] 495.1064 520.0664 500.9181 494.3690 499.6277 510.0352 488.5756 511.4469
## [185] 512.6070 506.6462 507.5022 486.0970 508.1884 490.5134 528.7434 502.3748
## [193] 507.4588 511.9495 506.2740 491.8927 515.8246 495.8567 480.8586 483.1961
## [201] 495.5964 472.5592 496.2202 491.8540 517.0957 503.4287 506.3775 500.8015
## [209] 493.7521 493.2759 502.9768 487.0085 509.8544 513.4243 507.3305 523.4857
## [217] 488.5249 509.0557 504.6014 510.7668 514.4822 503.2407 491.7934 495.9455
## [225] 492.1594 504.4261 496.2538 508.5467 501.8943 496.7091 481.7504 496.9663
## [233] 497.9031 492.6342 496.3270 509.6816 507.5405 510.3359 502.0057 510.3409
## [241] 514.4640 524.3633 491.5444 504.5871 508.4064 490.9840 490.8600 506.6702
## [249] 505.1595 494.7776 495.4432 480.4986 510.1816 482.5929 497.7654 511.9999
## [257] 506.3590 501.3101 513.2995 499.2053 500.4098 492.7491 502.9792 483.8177
## [265] 496.2295 490.4868 474.4191 492.1525 495.4626 518.2372 489.6109 510.5288
## [273] 483.3764 504.6137 486.5494 502.9036 502.1018 513.1999 507.8078 489.1935
## [281] 489.6629 487.2881 499.8138 499.9587 490.6205 491.6369 523.8604 520.3504
## [289] 514.4901 506.2440 491.7809 495.9371 502.5167 511.3595 499.5344 496.2050
## [297] 497.7392 492.1794 511.3939 489.2557 484.4992 511.1986 506.6688 503.4790
## [305] 496.5267 496.4268 501.9112 493.4915 508.9615 489.3944 497.7125 484.7137
## [313] 500.9224 487.5402 517.6414 499.3066 502.9916 499.6452 505.1212 491.5848
## [321] 511.1676 503.4239 499.3350 489.6853 493.2439 506.9204 505.1100 502.7789
## [329] 505.1365 486.7365 502.9121 484.3798 510.2866 500.2780 505.3189 513.5406
## [337] 511.6578 496.0741 506.5233 491.0493 497.8356 504.0819 493.8665 513.5820
## [345] 496.7030 495.5152 512.8421 506.3420 496.4141 501.9628 507.6866 507.3203
## [353] 513.0844 492.1879 497.4630 494.4730 504.8051 510.7993 499.9854 487.2446
## [361] 492.5096 504.9397 501.4696 499.9793 502.1932 495.7839 504.9490 501.9872
## [369] 486.7964 513.9956 499.9613 508.8108 498.9936 486.5213 487.7421 511.3348
## [377] 514.2973 493.8733 504.0669 498.0867 491.0162 490.9585 484.9427 497.2517
## [385] 484.6128 488.4277 516.2795 502.4150 511.4415 500.1109 490.4398 501.4483
## [393] 493.4203 497.0377 504.2191 483.2627 504.3651 501.5104 519.9230 517.1631
## [401] 507.9680 496.1063 502.0838 498.3456 491.9401 502.3809 492.3996 512.2937
## [409] 489.4481 525.1556 503.4904 507.6321 490.6536 497.7560 489.7130 498.0239
## [417] 477.4069 492.8480 497.4067 485.6590 507.2099 506.2567 510.4432 491.7937
## [425] 504.4263 493.0971 514.4371 505.6260 505.8947 498.2039 493.4503 505.0871
## [433] 491.4161 485.4894 497.8053 502.5865 499.8617 495.0815 516.8880 489.6799
## [441] 499.0095 493.0743 507.2926 493.1643 497.9580 515.3370 501.8053 485.5356
## [449] 498.0341 513.1337 516.9554 493.3367 500.5774 489.0343 495.5049 514.6211
## [457] 508.5642 512.3770 495.5374 501.1216 502.4233 486.6420 519.4570 511.6815
## [465] 496.5157 492.0769 503.9209 479.7379 496.7216 504.4532 473.0450 508.2426
## [473] 499.2113 515.3421 515.5860 493.4525 497.2558 514.5523 487.8463 508.9620
## [481] 494.7657 497.0378 493.9139 510.7959 506.4846 507.5910 496.6544 513.1127
## [489] 513.1534 512.2481 490.8319 480.8044 496.0866 493.3643 494.1482 509.3048
## [497] 495.9269 511.8133 501.9391 505.1529
mean(sim_berat)
## [1] 499.8015
sd(sim_berat)
## [1] 9.741094
hist(sim_berat,
     main = "Simulasi Distribusi Normal",
     xlab = "Berat Produk (Gram)",
     col = "lightgreen",
     prob = TRUE)
lines(density(sim_berat), col = "red", lwd = 2)

###Hasil simulasi menunjukkan nilai rata-rata (mean) sebesar 499.80, yang sangat mendekati target ideal pada variabel mean_val (500), serta nilai standar deviasi (sd) sebesar 9.74 yang juga mendekati parameter sd_val (10). Selisih yang sangat kecil ini membuktikan bahwa model simulasi mampu mereplikasi distribusi berat produk secara akurat dengan tingkat variasi yang terkendali. Secara visual, data ini membentuk kurva lonceng yang simetris pada grafik histogram, yang menandakan bahwa proses pengemasan produk berlangsung stabil dan konsisten di sekitar nilai rata-ratanya.

##Buat studi kasus sendiri yang melibatkan simulasi variabel random dari distribusi yang telah dipelajari. ###Sebagai seorang desainer grafis yang sering mengunggah file berukuran besar, kecepatan internet sangatlah krusial. Dalam studi kasus ini, dilakukan simulasi terhadap kecepatan unduh (download speed) provider internet selama 1.000 kali pengujian untuk melihat konsistensi layanannya. Diasumsikan kecepatan rata-rata adalah 75 Mbps dengan standar deviasi 5 Mbps. ###mean_speed <- 75 (rata-rata kecepatan dalam Mbps) ###sd_speed <- 5 (standar deviasi) ###n_simulasi <- 1000

set.seed(83)
mean_speed <- 75
sd_speed <- 5
sim_internet <- rnorm(1000, mean = mean_speed, sd = sd_speed)
sim_internet
##    [1] 63.12903 75.31650 74.71635 75.97155 80.65757 70.14404 84.18012 72.97392
##    [9] 77.90919 78.37895 76.37435 70.18923 79.77308 75.41640 82.73592 83.53372
##   [17] 67.90211 74.49415 87.53050 76.00681 74.66149 77.99779 80.34244 78.48616
##   [25] 80.10714 76.26059 78.60785 72.92052 71.16847 65.62225 78.30162 66.94338
##   [33] 71.45471 78.77350 78.74554 75.97088 69.57791 81.82005 66.89625 75.10974
##   [41] 75.96139 66.82357 70.27620 76.87094 72.31508 74.56529 86.34546 79.65622
##   [49] 76.33566 78.07130 77.57986 87.51712 80.15304 80.18658 79.55113 69.78662
##   [57] 77.22548 77.92113 76.52178 75.07901 74.67914 87.19962 77.16638 76.62768
##   [65] 77.40555 74.05148 73.78420 72.06310 76.25245 63.07283 73.85497 65.57522
##   [73] 68.67520 74.21691 71.07772 69.88958 77.09963 77.51760 81.12167 76.98313
##   [81] 78.25153 72.79651 69.35540 81.60630 78.83595 77.30825 80.53705 78.33875
##   [89] 78.78451 81.31565 75.03811 70.40053 70.62412 68.77596 66.83787 81.06421
##   [97] 72.79280 84.37714 72.29921 76.57067 82.58340 69.86328 80.18350 70.97193
##  [105] 81.01638 79.02461 61.23478 86.56162 66.86255 73.08798 84.01385 76.74114
##  [113] 76.20901 80.93214 78.94062 78.07386 77.13008 79.56289 82.36455 81.96990
##  [121] 73.69193 67.15587 74.80991 74.95316 76.35269 77.25164 83.04414 74.11652
##  [129] 73.28942 73.89151 83.13368 73.21418 72.71019 83.59944 70.14726 74.50369
##  [137] 70.84813 77.09069 69.99769 76.88686 74.68785 74.39721 85.41689 68.20329
##  [145] 67.11635 81.61818 75.82674 74.08495 74.77739 74.64810 74.82730 74.24177
##  [153] 70.12953 71.27477 75.64924 59.19033 78.20788 65.58676 74.14214 75.38989
##  [161] 74.44978 72.60315 73.50662 73.32030 74.10157 76.90971 81.91649 68.38753
##  [169] 74.56125 78.14436 67.10253 80.01691 74.94915 77.95067 78.75422 80.56936
##  [177] 74.23089 68.89550 67.62112 77.70539 73.47991 76.74993 75.85111 70.10540
##  [185] 80.53928 68.88226 79.65069 80.27729 78.88031 65.08603 68.49722 75.23554
##  [193] 83.72103 79.99232 73.65833 74.52053 72.71756 72.54299 74.52566 75.06333
##  [201] 72.10454 78.50881 71.98203 69.59703 75.04983 73.92970 80.00610 73.39743
##  [209] 79.58378 69.42403 74.30395 80.56110 84.39951 83.86360 77.94015 66.60873
##  [217] 74.51130 81.60161 73.44933 76.75198 76.32377 65.78958 79.07427 80.90816
##  [225] 74.63649 78.60652 73.27840 74.56952 80.75755 78.64655 81.25717 72.33057
##  [233] 74.83654 80.54709 70.87837 72.32706 69.62897 77.02488 80.34367 82.50792
##  [241] 72.63939 66.55941 76.33966 80.60934 81.65732 77.33713 77.93807 71.22398
##  [249] 84.29558 76.11145 82.56034 73.38799 74.86110 73.85244 78.63482 71.58158
##  [257] 78.69778 78.17672 77.90892 77.23886 77.44966 70.80438 70.47969 66.04894
##  [265] 73.49361 66.69090 73.59549 72.62629 77.24796 74.18390 77.56350 81.47474
##  [273] 75.96038 70.73687 71.62788 72.16184 82.40894 73.57458 77.04486 85.68790
##  [281] 70.14221 74.40753 75.81059 78.12710 81.13018 59.62075 65.66767 76.54696
##  [289] 73.98679 75.69540 77.75492 76.39944 80.05757 70.60114 68.71711 75.46500
##  [297] 74.47342 71.04437 76.39004 73.37305 68.88031 69.75283 75.08535 83.18475
##  [305] 70.20086 77.29624 74.18517 66.09006 65.40834 74.79744 72.70659 77.98643
##  [313] 73.42857 66.06120 89.29740 86.34542 77.68375 68.95780 79.74720 69.24459
##  [321] 72.68116 78.53937 74.48725 75.92127 70.39742 86.87208 72.77546 78.22797
##  [329] 78.93672 75.96445 74.87171 74.40739 67.80425 84.43627 79.77079 72.66724
##  [337] 78.04525 79.42467 82.10072 66.61069 75.87328 66.91885 72.49019 84.86858
##  [345] 82.28211 67.96795 68.05922 62.32992 72.02713 76.09235 67.28739 78.00491
##  [353] 78.44008 65.52187 79.63928 67.01790 73.77276 73.86382 64.26426 75.61403
##  [361] 75.95130 82.73709 75.86002 70.16693 70.98378 69.69886 73.35435 72.02386
##  [369] 72.01245 72.29099 77.47236 75.08961 75.10227 80.89914 82.07675 85.00449
##  [377] 69.21139 79.33355 73.26612 75.55105 67.20227 72.27449 75.36432 83.60932
##  [385] 75.49109 73.72158 80.34745 68.85769 79.26814 84.42538 76.53614 69.35582
##  [393] 74.94311 76.55844 77.81207 66.79433 75.65199 73.19614 80.04421 70.62084
##  [401] 67.89751 69.65141 74.72310 66.84891 67.96026 65.09277 71.60033 69.73350
##  [409] 75.34580 70.20329 71.86826 76.07931 82.17158 80.59005 77.99318 79.98143
##  [417] 80.74845 82.20377 71.47895 75.54170 86.78335 75.81822 79.09525 84.02098
##  [425] 67.27497 78.84068 78.40051 74.64992 78.38561 72.63370 72.99491 71.82941
##  [433] 80.80463 79.27390 82.38007 76.92503 75.89964 68.35838 74.68337 75.88181
##  [441] 79.96401 78.45258 66.75827 66.66621 72.10259 69.67364 73.47343 72.78522
##  [449] 85.99540 84.29334 90.35398 85.23813 78.47748 73.57939 72.89819 77.39574
##  [457] 74.68255 69.56636 72.66251 67.12831 78.76904 71.59915 71.82714 79.53961
##  [465] 82.56925 78.97835 80.23962 66.73428 73.64177 72.02337 74.43972 71.84323
##  [473] 70.16245 78.75121 68.90476 79.61736 73.20362 74.20323 73.67183 71.50222
##  [481] 78.95017 81.38248 78.16625 81.42673 79.86545 76.23797 83.57907 72.88555
##  [489] 70.29120 73.15161 76.45088 78.62346 73.99217 81.83403 87.06497 72.40057
##  [497] 69.67175 73.79651 66.47495 73.53817 79.36640 69.94328 72.99297 69.52155
##  [505] 81.16892 75.46437 87.11431 73.70665 75.91616 79.95642 78.04266 70.92478
##  [513] 82.59110 68.04374 72.73017 74.26194 72.27369 76.50009 80.49999 68.49444
##  [521] 74.50484 82.88713 77.46819 69.18568 78.27424 71.05682 75.37728 75.09677
##  [529] 80.76838 68.95457 74.37117 67.49836 72.58751 74.16773 78.62173 74.58910
##  [537] 76.35032 75.81747 83.47118 77.91800 77.04191 76.39663 81.27328 66.18857
##  [545] 70.99267 74.79955 71.88868 78.18569 78.80717 76.55489 79.77494 67.33264
##  [553] 73.65623 77.78837 75.79919 74.74691 83.99458 71.77502 73.66083 74.41276
##  [561] 80.26238 66.70894 77.70592 74.91261 75.65631 81.96549 62.62216 79.66042
##  [569] 75.12293 77.54670 71.61539 70.93091 75.35210 64.98983 71.20637 74.40272
##  [577] 76.37704 83.75394 80.65292 76.20660 71.11137 72.26132 83.68468 78.62201
##  [585] 71.16249 74.32125 74.95455 74.43743 67.36446 75.05889 72.45196 71.02174
##  [593] 78.80567 79.86515 76.18939 78.62299 74.88512 73.24382 74.34603 76.22138
##  [601] 78.50757 75.84376 76.61951 71.27687 72.84993 73.26232 74.68006 77.42329
##  [609] 77.80014 73.17766 81.33224 79.12244 74.39448 75.11587 79.85258 72.28142
##  [617] 74.17024 82.30009 67.62067 76.20243 82.52294 84.11969 80.27143 81.14297
##  [625] 80.08031 84.20850 76.20272 64.83789 72.45787 67.87106 76.44557 76.92079
##  [633] 70.60572 83.27932 74.88476 69.02466 71.56616 68.74199 69.11863 80.70267
##  [641] 71.07956 78.12219 72.38748 76.25147 79.94790 74.69844 67.27644 72.96682
##  [649] 72.34590 75.34124 72.48686 75.71636 76.98465 75.26625 68.35360 81.46428
##  [657] 75.76699 71.40761 72.46876 79.84651 74.55661 71.61707 72.46070 77.45255
##  [665] 72.59378 75.37660 74.64067 75.31453 68.62325 70.45743 72.11600 74.31158
##  [673] 73.59264 66.39851 72.41014 71.93370 68.13859 73.68803 86.86442 83.35852
##  [681] 75.72246 76.79575 77.64988 73.37793 68.40067 78.53677 75.83879 81.07118
##  [689] 65.11680 78.61286 76.08799 72.56316 73.29564 72.08348 78.97028 75.73147
##  [697] 73.68940 66.87215 76.07787 67.67585 75.63841 76.72338 77.34067 78.66103
##  [705] 70.18915 68.03915 70.95590 73.73800 75.44901 66.54428 76.69234 76.33443
##  [713] 71.00283 74.09729 81.36496 71.67333 76.64638 67.18352 85.38885 75.11977
##  [721] 67.76371 65.40502 79.77322 81.06891 80.85695 80.34673 73.10329 79.33520
##  [729] 72.59098 84.76393 75.80761 81.24021 66.56120 73.01436 78.46832 82.97871
##  [737] 71.50067 79.76119 75.27961 83.15201 68.47890 75.32162 71.51729 80.05071
##  [745] 69.94589 74.48000 73.03174 73.91866 68.22023 77.00710 65.13919 73.19497
##  [753] 68.71462 67.56669 81.34733 76.33628 73.78304 78.12902 73.54977 77.27002
##  [761] 72.61719 81.14269 75.41415 78.69105 75.03092 77.11754 71.25795 80.47349
##  [769] 75.94874 71.72216 73.69789 69.52384 70.37888 73.42179 70.92798 67.00919
##  [777] 74.73041 77.73187 78.21148 78.85328 80.88971 72.86637 88.05679 75.37756
##  [785] 72.91726 70.17481 67.01198 68.80732 66.81863 73.36836 71.18065 76.85840
##  [793] 77.29083 77.93345 66.61563 70.42967 76.77490 69.14436 72.59541 77.04007
##  [801] 74.82692 70.60176 74.49293 71.54886 72.68429 78.85898 72.99935 76.69956
##  [809] 82.06871 72.35754 77.55142 74.18977 85.52028 64.83787 81.95515 78.09215
##  [817] 80.36577 69.60784 63.19630 66.91426 78.41554 79.72154 80.27602 70.80863
##  [825] 69.97568 71.79572 72.79885 79.38994 78.18286 78.33410 72.42730 69.38924
##  [833] 74.51505 68.39211 74.64680 81.77921 69.79291 76.71691 75.80781 80.27397
##  [841] 74.69922 85.16883 77.15839 71.10861 74.23617 71.69930 74.44018 72.67607
##  [849] 77.84827 67.41952 77.30591 72.88821 79.52619 76.38998 73.23682 63.38887
##  [857] 71.59267 85.27664 71.66924 83.49347 77.14858 67.44388 70.02119 80.07287
##  [865] 79.29073 82.70148 74.19960 77.68095 79.37374 71.94822 79.19222 77.08839
##  [873] 72.27318 71.96773 78.69099 77.24626 67.69173 71.87833 75.20077 72.39017
##  [881] 74.07151 92.40211 80.65958 71.84578 74.74587 69.06541 85.03507 78.81156
##  [889] 80.86560 69.54967 78.13486 76.21197 75.95333 75.88108 77.96407 81.59410
##  [897] 79.28319 77.08831 74.09725 74.33515 76.06797 77.82114 72.34673 75.47436
##  [905] 67.25061 79.98089 76.31895 77.19924 76.23565 79.66660 79.43408 82.29631
##  [913] 65.32308 76.81959 77.37033 79.20118 77.31790 69.86936 78.24084 67.02470
##  [921] 77.23956 82.64558 68.82850 80.78020 69.20092 75.91497 82.82950 74.05747
##  [929] 74.52045 74.87764 82.22743 73.50639 75.89349 77.12755 75.27595 76.31733
##  [937] 71.98071 73.59701 68.44806 74.52782 66.20307 77.43564 76.14733 71.58013
##  [945] 74.66710 71.20685 78.97413 73.31316 79.19104 74.46095 65.40955 70.47284
##  [953] 72.91233 80.63104 75.53614 88.41433 69.54093 80.22116 70.53010 82.41112
##  [961] 70.53644 67.19538 82.89170 72.31663 80.84315 74.52633 79.44637 75.54737
##  [969] 74.62747 73.42762 67.97671 67.55213 75.43285 76.84402 75.68771 70.09804
##  [977] 87.06246 66.02660 74.73683 72.13452 81.61104 73.16224 62.84125 77.28539
##  [985] 79.55460 70.82148 76.14143 79.57638 70.94008 73.08022 75.31570 82.25310
##  [993] 84.44642 77.51322 79.80540 72.22568 74.02219 81.89152 78.75259 75.46391
mean(sim_internet)
## [1] 75.17409
sd(sim_internet)
## [1] 5.02768
hist(sim_internet, 
     main = "Simulasi Kecepatan InternetD", 
     xlab = "Kecepatan (Mbps)", 
     col = "skyblue", 
     prob = TRUE)
lines(density(sim_internet), col = "blue", lwd = 2)

###Hasil simulasi menunjukkan nilai rata-rata (mean) sebesar 75.17 Mbps dan standar deviasi (sd) sebesar 5.02 Mbps, yang membuktikan bahwa model ini sangat akurat karena hampir identik dengan parameter yang ditentukan. Secara teknis, ini mengindikasikan bahwa koneksi internet memiliki performa yang sangat stabil dengan fluktuasi yang sangat minim di sekitar nilai target. Visualisasi melalui kurva lonceng pada histogram mengonfirmasi bahwa distribusi kecepatan internet tersebar secara normal dan konsisten, menjadikannya model yang reliabel untuk menggambarkan kualitas layanan provider tersebut.