optimasi sebagai fungsi dari kalkulus

Nama dan NIM : Nadia Din Salima Al Kamila (230605110140)

Dosen Pengampu : Prof. Dr. Suhartono, M.Kom

Universitas : Universitas Islam Negeri Maulana Malik Ibrahim Malang

Fakultas : Sains dan Teknologi

Program Studi : Teknik Informatika

library(mosaicCalc)

## Loading required package: mosaic

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

## 
## The 'mosaic' package masks several functions from core packages in order to add 
## additional features.  The original behavior of these functions should not be affected by this.

## 
## Attaching package: 'mosaic'

## The following objects are masked from 'package:dplyr':
## 
##     count, do, tally

## The following object is masked from 'package:Matrix':
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##     mean

## The following object is masked from 'package:ggplot2':
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##     stat

## The following objects are masked from 'package:stats':
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##     binom.test, cor, cor.test, cov, fivenum, IQR, median, prop.test,
##     quantile, sd, t.test, var

## The following objects are masked from 'package:base':
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##     max, mean, min, prod, range, sample, sum

## Loading required package: mosaicCore

## 
## Attaching package: 'mosaicCore'

## The following objects are masked from 'package:dplyr':
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## The legacy packages maptools, rgdal, and rgeos, underpinning the sp package,
## which was just loaded, will retire in October 2023.
## Please refer to R-spatial evolution reports for details, especially
## https://r-spatial.org/r/2023/05/15/evolution4.html.
## It may be desirable to make the sf package available;
## package maintainers should consider adding sf to Suggests:.
## The sp package is now running under evolution status 2
##      (status 2 uses the sf package in place of rgdal)

## 
## Attaching package: 'mosaicCalc'

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

# Optimasi
# Masalah optimasi terdiri dari fase pemodelan dan fase solusi.

#Optimsasi grafis

# Carilah puncak lokal, lalu baca masukan yang menghasilkan nilai di puncak tersebut.

# Optimasi numerik

# Terkait fungsi, maksimalisasi adalah proses menemukan masukan ke fungsi yang menghasilkan keluaran lebih besar daripada masukan terdekat lainnya.

h <- rfun(~ x, seed=7293)
argM(h(x) ~ x, bounds(x=-5:5))

## # A tibble: 2 × 3
##        x .output. concavity
##    <dbl>    <dbl>     <dbl>
## 1 -1.68      1.93         1
## 2  0.173     8.25        -1

## # A tibble: 2 × 3
##        x .output. concavity
##    <dbl>    <dbl>     <dbl>
## 1 -1.68      1.93         1
## 2  0.173     8.25        -1

x <- seq(-3, 0, by = 0.1)

y <- sin(x) + sin(2*x)

plot(x, y, type = "l", col = "purple", lwd = 2, xlab = "Nilai x", ylab = "Nilai f(x)", main = "Grafik Fungsi f(x)")

Minimalisasi mengacu pada teknik yang sama, tetapi di mana garis vertikal ditarik pada titik terdalam di setiap “lembah” grafik fungsi. Nilai input yang terletak di salah satu lembah tersebut disebut argmin.

Optimasi adalah istilah umum yang mencakup maksimalisasi dan minimalisasi. ```