SELECTION SORT
Metode seleksi adalah pengurutan data dengan cara mencari data yang terkecil kemudian menukarnya dengan data yang digunakan sebagai acuan (pivot).
Proses dari Selection Sort Ascending adalah sebagai berikut :
1. Mencari data terkecil dari data pertama sampai dengan data yang terakhir. Kemudian posisinya ditukar dengan data yang pertama.
2. Mencari data terkecil dari data kedua sampai dengan data terakhir, kemudian posisinya ditukar dengan data yang kedua.
3. Mencari data terkecil dari data ketiga sampai dengan data terakhir, kemudian posisinya ditukar dengan data yang ketiga.
4. Begitu seterusnya sampai semua data terurut naik. Apabila terdapat n buah data yang akan diurutkan, maka membutuhkan (n-1) langkah pengurutan, dengan data terakhir, yaitu data ke n tidak perlu diurutkan karena hanya tinggal data satu-satunya.
Untuk proses dari Selection Sort Descending (mencari data terbesar) adalah kebalikan dari proses di atas.
Sebagai contoh :
Terdapat suatu variable array dimana nilai dalam array tersebut :
NILAI[8] = { 44, 55, 12, 42, 94, 18, 6, 67 }
Penyelesaiannya adalah :
![](data:image/png;base64,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)
Agar lebih jelasnya kita langsung saja ke studi kasusnya dan source codenya pada borland C++ :
Selection Sort Ascending
Inputkan banyaknya data yang akan dilakukan sorting (max. 10). Inputkan data sesuai dengan banyaknya data yang diminta, kemudian urutkanlah data tersebut dari yang terkecil ke yang terbesar!
Source code :
#include<iostream.h>
#include<conio.h>
int data[10];
int n;
void tukar(int a, int b)
{
int t;
t=data[b];
data[b]=data[a];
data[a]=t;
}
void main()
{
int pos,i,j;
cout<<"-------------------------------------------------"<<endl;
cout<<"SELECTION SORT ASCENDING"<<endl;
cout<<"-------------------------------------------------"<<endl;
cout<<"INPUTKAN BANYAK DATA = ";
cin>>n;
cout<<"-------------------------------------------------"<<endl;
for(int i=0;i<n;i++)
{
cout<<"INPUTKAN DATA KE-"<<(i+1)<<" = " ;
cin>>data[i];
}
cout<<"-------------------------------------------------"<<endl;
cout<<"DATA YANG DIINPUTKAN :"<<endl;
for(i=0;i<n;i++)
{
cout<<data[i]<<" ";
}
cout<<endl<<"-------------------------------------------------"<<endl;
for(i=0;i<n-1;i++)
{
pos=i;
for(j=i+1;j<n;j++)
{
if(data[j]<data[pos])pos=j;
}
if(pos!=i) tukar(pos,i);
}
cout<<"DATA YANG TELAH DIURUTKAN SECARA ASCENDING : "<<endl;
for(int i=0;i<n;i++)
{
cout<<data[i]<<" ";
}
cout<<endl;
cout<<"-------------------------------------------------"<<endl;
cout<<"SELECTION SORT SELESAI !"<<endl;
cout<<"-------------------------------------------------"<<endl;
getch();
}
Berikut ini hasil dari source code di atas :
Selection Sort Descending
Buatlah program seperti diatas, tetapi urutkan data dari yang terbesar ke terkecil.
Source code :
#include<iostream.h>
#include<conio.h>
int data[10];
int n;
void tukar(int a, int b)
{
int t;
t=data[b];
data[b]=data[a];
data[a]=t;
}
void main()
{
int pos,i,j;
cout<<"-------------------------------------------------"<<endl;
cout<<"SELECTION SORT DESCENDING"<<endl;
cout<<"-------------------------------------------------"<<endl;
cout<<"INPUTKAN BANYAK DATA = ";
cin>>n;
cout<<"-------------------------------------------------"<<endl;
for(int i=0;i<n;i++)
{
cout<<"INPUTKAN DATA KE-"<<(i+1)<<" = " ;
cin>>data[i];
}
cout<<"-------------------------------------------------"<<endl;
cout<<"DATA YANG DIINPUTKAN :"<<endl;
for(i=0;i<n;i++)
{
cout<<data[i]<<" ";
}
cout<<endl<<"-------------------------------------------------"<<endl;
for(i=0;i<n-1;i++)
{
pos=i;
for(j=i+1;j<n;j++)
{
if(data[j]>data[pos])pos=j;
}
if(pos!=i) tukar(pos,i);
}
cout<<"DATA YANG TELAH DIURUTKAN SECARA DESCENDING : "<<endl;
for(int i=0;i<n;i++)
{
cout<<data[i]<<" ";
}
cout<<endl;
cout<<"-------------------------------------------------"<<endl;
cout<<"SELECTION SORT SELESAI !"<<endl;
cout<<"-------------------------------------------------"<<endl;
getch();
}
Hasilnya jika telah di run adalah :
INSERTION SORT
Pada metode insertion sort, proses pengurutannya dimulai dari data ke-2 (indeks ke-1), kemudian disisipkan pada tempat yang sesuai. Dan data pertama (data pada indeks ke-0) dianggap sudah pada tempatnya.
Kita coba saja langsung ke studi kasus dan source codenya :
Insertion Sort Ascending
Studi Kasus :
Buatlah program seperti selection di atas, dan urutkan data tersebut dari terkecil ke terbesar dengan menggunakan metode insertion sort.
Source code :
#include<iostream.h>
#include<conio.h>
int data[10];
int n;
void main()
{
int tmp,i,j;
cout<<"-------------------------------------------------"<<endl;
cout<<"INSERTION SORT ASCENDING"<<endl;
cout<<"-------------------------------------------------"<<endl;
cout<<"INPUTKAN BANYAKNYA DATA = ";
cin>>n;
cout<<"-------------------------------------------------"<<endl;
for(int i=0;i<n;i++)
{
cout<<"INPUTKAN DATA KE-"<<(i+1)<<" = " ;
cin>>data[i];
}
cout<<"-------------------------------------------------"<<endl;
cout<<"DATA YANG DIINPUTKAN :"<<endl;
for(i=0;i<n;i++)
{
cout<<data[i]<<" ";
}
cout<<endl<<"-------------------------------------------------"<<endl;
for(i=1;i<n;i++)
{
tmp=data[i];
j=i-1;
while(data[j]>tmp && j>=0)
{
data[j+1]=data[j];
j--;
}
data[j+1]=tmp;
}
cout<<"DATA YANG TELAH DIURUTKAN SECARA ASCENDING : "<<endl;
for(int i=0;i<n;i++)
{
cout<<data[i]<<" ";
}
cout<<endl;
cout<<"-------------------------------------------------"<<endl;
cout<<"INSERTION SORT SELESAI !"<<endl;
cout<<"-------------------------------------------------"<<endl;
getch();
}
Berikut adalah hasilnya jika di run :
Insertion Sort Descending
Studi kasus :
Buatlah program yang sama, tetapi urutkan dari yang terbesar ke terkecil.
Source code :
#include<iostream.h>
#include<conio.h>
int data[10];
int n;
void main()
{
int tmp,i,j;
cout<<"-------------------------------------------------"<<endl;
cout<<"INSERTION SORT DESCENDING"<<endl;
cout<<"-------------------------------------------------"<<endl;
cout<<"INPUTKAN BANYAKNYA DATA = ";
cin>>n;
cout<<"-------------------------------------------------"<<endl;
for(int i=0;i<n;i++)
{
cout<<"INPUTKAN DATA KE-"<<(i+1)<<" = " ;
cin>>data[i];
}
cout<<"-------------------------------------------------"<<endl;
cout<<"DATA YANG DIINPUTKAN :"<<endl;
for(i=0;i<n;i++)
{
cout<<data[i]<<" ";
}
cout<<endl<<"-------------------------------------------------"<<endl;
for(i=1;i<n;i++)
{
tmp=data[i];
j=i-1;
while(data[j]<tmp && j>=0)
{
data[j+1]=data[j];
j--;
}
data[j+1]=tmp;
}
cout<<"DATA YANG TELAH DIURUTKAN SECARA DESCENDING : "<<endl;
for(int i=0;i<n;i++)
{
cout<<data[i]<<" ";
}
cout<<endl;
cout<<"-------------------------------------------------"<<endl;
cout<<"INSERTION SORT SELESAI !"<<endl;
cout<<"-------------------------------------------------"<<endl;
getch();
}
Berikut hasilnya jika di run :
BUBBLE SORT :
Dalam bubble sort, prosesnya adalah selalu membandingkan 2 data yang berdekatan atau disebelahnya.
Lebih jelasnya langsung saja ke studi kasus dan source codenya.
Bubble Sort Ascending
Studi Kasus :
Buatlah program seperti selection dan insertion sort di atas dengan menggunakan metode bubble sort, dan urutkan data tersebut dari yang terkecil ke terbesar.
Source code :
#include<iostream.h>
#include<conio.h>
int data[20];
int n;
void main()
{
int i, j, tmp;
cout<<"---------------------------------------------"<<endl;
cout<<"BUBBLE SORT ASCENDING"<<endl;
cout<<"---------------------------------------------"<<endl;
cout<<"INPUTKAN BANYAKNYA DATA : ";
cin>>n;
cout<<"---------------------------------------------"<<endl;
for(i=0; i<n; i++)
{
cout<<"INPUTKAN BILANGAN KE-["<<(i+1)<<"] : ";
cin>>data[i];
}
cout<<"---------------------------------------------"<<endl;
cout<<"DATA YANG DIINPUTKAN : "<<endl;
for(i=0; i<n; i++)
{
cout<<data[i]<<" ";
}
cout<<endl<<"---------------------------------------------"<<endl;
for(i=0; i<n; i++)
{
for(j=i+1; j<n; j++)
{
if(data[i]>data[j])
{
tmp = data[i];
data[i] = data[j];
data[j] = tmp;
}
}
}
cout<<"DATA SETELAH DIURUTKAN SECARA ASCENDING : "<<endl;
for(i=0; i<n; i++)
{
cout<<data[i]<<" ";
}
cout<<endl<<"---------------------------------------------"<<endl;
cout<<"BUBBLE SORT SELESAI !"<<endl;
cout<<"---------------------------------------------"<<endl;
getch();
}
Berikut hasilnya jika di run :
Bubble Sort Descending
Studi kasus :
Buatlah program seperti di atas, kemudian urutkan data dari terbesar ke terkecil.
Source code :
#include<iostream.h>
#include<conio.h>
int data[20];
int n;
void main()
{
int i, j, tmp;
cout<<"---------------------------------------------"<<endl;
cout<<"BUBBLE SORT DESCENDING"<<endl;
cout<<"---------------------------------------------"<<endl;
cout<<"INPUTKAN BANYAKNYA DATA : ";
cin>>n;
cout<<"---------------------------------------------"<<endl;
for(i=0; i<n; i++)
{
cout<<"INPUTKAN BILANGAN KE-["<<(i+1)<<"] : ";
cin>>data[i];
}
cout<<"---------------------------------------------"<<endl;
cout<<"DATA YANG DIINPUTKAN : "<<endl;
for(i=0; i<n; i++)
{
cout<<data[i]<<" ";
}
cout<<endl<<"---------------------------------------------"<<endl;
for(i=0; i<n; i++)
{
for(j=i+1; j<n; j++)
{
if(data[i]<data[j])
{
tmp = data[i];
data[i] = data[j];
data[j] = tmp;
}
}
}
cout<<"DATA SETELAH DIURUTKAN SECARA DESCENDING : "<<endl;
for(i=0; i<n; i++)
{
cout<<data[i]<<" ";
}
cout<<endl<<"---------------------------------------------"<<endl;
cout<<"BUBBLE SORT SELESAI !"<<endl;
cout<<"---------------------------------------------"<<endl;
getch();
}
Dan berikut hasil dari source code di atas jika di run :
![](data:image/png;base64,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)
Quick Sort
Algoritma metode quick sort c++ diperkenalkan pertama kali oleh C.A.R. Hoare pada tahun 1960. Program quick sort c ++ adalah algoritma sorting yang berdasarkan pembandingan dengan metode divide and conquer (bagi dan kuasai). Disebut metode Quick Sort, karena Algoritma quick sort mengurutkan dengan sangat cepat. metode Quick sort c++ disebut juga dengan partition exchange sort, karena konsepnya membuat partisi-partisi, dan sorting dilakukan per partisi.
Contoh Algoritma Quick Sort C++
metode quick sort c++ mengurutkan dengan sangat cepat, namun algoritma ini sangat komplex dan diproses secara rekursif. Dapat memungkinkan untuk menulis algoritma yang lebih cepat untuk beberapa kasus khusus. Tapi untuk kasus umum, sampai saat ini tidak ada yang lebih cepat dibandingkan algoritma metode quick sort c++.
Apa itu Pivot ?
Apa itu Pivot ?
Pada algoritma quick sort, pemilihan pivot ialah hal yang menentukan apakah algoritma quick sort tersebut akan memberikan performa terbaik atau terburuk. Berikut beberapa cara pemilihan pivot :
- Pivot merupakan elemen pertama, elemen terakhir, atau elemen tengah dalam array. Cara ini bagus jika elemen tabel tersusun secara acak, tetapi sebaliknya atau tidak bagus jika elemen tabel semula sudah terurut.
- Pivot dipilih dengan cara acak dari salah satu elemen array. Cara ini baik tapi belum tentu maksimal, sebab diperlukan prosedur khusus untuk menentukan pivot secara acak.
- Pivot adalah elemen median tabel. Cara ini yaitu cara paling bagus, sebab pada hasil partisi menghasilkan dua bagian tabel yang berukuran seimbang. Juga cara ini memberikan kompleksitas waktu yang minimum. Masalahnya, mencari median dari elemen tabel yang belum terurut adalah persoalan tersendiri
Contoh program quick sort
#include <iostream>
#include <conio.h>
using namespace std;
void quick_sort(int arr[], int left, int right)
{
int i = left, j = right;int tmp;
int pivot = arr[(left+right)/2];/* partition */
while (i<j){
while (arr[i] < pivot)
i++;
while (arr[j] > pivot)
j--;
if (i<=j){
tmp = arr[i];
arr[i] = arr[j];
arr[j] = tmp;
i++;j--;
};
}; /* recursion */
if (left < j)
quick_sort(arr, left, j);
if (i < right)
quick_sort(arr, i, right);
}
int main()
{
int i,n,data[50];
cout<<"Masukan banyak data: ";cin>>n;
for(i=0;i<n;i++)
{cout<<"Masukan data ["<<i<<"] : ";cin>>data[i];}
cout<<"\nData sebelum diurutkan: "<<endl;
for(i=0;i<n;i++)
{
cout<<data[i]<<" ";
}cout<<"\n";
quick_sort(data,0,n-1);//hasil pengurutan
cout<<"\nHasil pengurutan:\n";
{
int i;
for (i=0;i<n;i++)
cout<<data[i]<<" ";
cout<<"\n";
}getch();
}
Output program quick sort
Marge Sort
Program Merge Sort C++ merupakan algoritma pengurutan dalam ilmu komputer yang dirancang untuk memenuhi kebutuhan pengurutan atas suatu rangkaian data yang tidak memungkinkan untuk ditampung dalam memori komputer karena jumlahnya yang terlalu besar. Algoritma program merge sort c++ ini ditemukan oleh John von Neumann tepat pada tahun 1945.
Algoritma coding merge sort bahasa c++ ini membagi (split) table menjadi dua tabel sama besar.
Masing-masing tabel diurutkan secara rekursif, dan kemudian digabungkan kembali untuk membentuk table yang terurut. Implementasi dasar dari algoritma marge sort c++ ini memakai tiga buah tabel, dua diantaranya untuk menyimpan elemen dari tabel yang telah dibagi dua dan satu untuk menyimpan elemen yang telah teurut. Namun metode program merge sort c++ ini bisa juga dilakukan langsung pada dua tabel, sehingga menghemat ruang atau memori yang dibutuhkan. Di bawah ini merupakan algoritma metode merge sort c++ yang dilakukan pada 2 tabel.
Algoritma Merge Sort C++ Dua Tabel
Algoritma Metode Merge sort c++ ini sebenernya lebih cepat dibandingkan heap sort untuk tabel yang lebih besar. Tetapi, algoritma ini membutuhkan setidaknya ruang / memori 2x lebih besar karena dilakukan secara rekursif dan juga memakai dua tabel. Hal ini menyebabkan algoritma ini kurang banyak dipakai.
Metode Merge sort menggabungkan 2 ide utama bertujuan untuk meningkatkan runtimenya:
- Array kecil mengambil langkah-langkah untuk menyortir lebih sedikit dari array besar.
- Dan Lebih sedikit langkah yang diperlukan untuk membangun sebuah data array terurut dari dua buah array terurut dari pada dari dua buah array tak terurut.
Contoh Program Marge Sort Pada C++
#include <iostream>
#include <conio.h>
using namespace std;
int a[50];
void merge(int,int,int);
void merge_sort(int low,int high)
{
int mid;
if(low<high)
{
mid=(low+high)/2;
merge_sort(low,mid);
merge_sort(mid+1,high);
merge(low,mid,high);
}
}
void merge(int low,int mid,int high)
{
int h,i,j,b[50],k;
h=low;
i=low;
j=mid+1;
while((h<=mid)&&(j<=high))
{
if(a[h]<=a[j])
{
b[i]=a[h]; h++;
}
else
{
b[i]=a[j]; j++;
} i++;
}
if(h>mid)
{
for(k=j;k<=high;k++)
{
b[i]=a[k]; i++;
}
}
else
{
for(k=h;k<=mid;k++)
{
b[i]=a[k]; i++;
}
}
for(k=low;k<=high;k++)
a[k]=b[k];
}
main()
{
int num,i;
cout<<"Hardifal "<<endl;
cout<<"---------------------------"<<endl;
cout<<" ALGORITMA MERGE SORT C++ "<<endl;
cout<<"---------------------------"<<endl;
cout<<endl;
cout<<"Masukkan Banyak Bilangan: ";cin>>num;
cout<<endl;
cout<<"Sekarang masukkan "<< num <<" Bilangan yang ingin Diurutkan :"<<endl;
for(i=1;i<=num;i++)
{
cout<<"Bilangan ke-"<<i<<" ";cin>>a[i] ;
}
merge_sort(1,num);
cout<<endl;
cout<<endl;
for(i=1;i<=num;i++)
cout<<a[i]<<" ";
cout<<endl<<endl<<endl<<endl;
}
Output Program Marge Sort
![](data:image/png;base64,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)