Senin, 28 Agustus 2023

Konversi Desimal ke Oktal

 Dengan rumus yang sama seperti biner kita bisa lakukan juga untuk bilangan berbasis 8 (oktal).

Contoh:

6710 = ……8 ?
  1. Pertama-tama 67/8 = 8, sisa 3
  2. Lalu 8/8 = 1, sisa 0,
  3. Terakhir 1/8=0, sisa 1.
  4. Dengan demikian dari hasil perhitungan didaptkan 6710 = 1038


Jumat, 25 Agustus 2023

Calculation of K-Nearest Neighbor with Minkowski Distance (5 Criteria)

In this post, I will discuss the calculation of K-Nearest Neighbor with Minkowski Distance using 5 criteria.

The classification that will be discussed is the Classification of Scholarship Recipients.

The data we will use is:
  • Consists of 10 data
  • Consists of 5 criteria
  • K = 5
  • r Minkowski = 3


Information :
  • Which will be categorized consists of Mathematics scores, Indonesian scores, English scores, Science scores and Non-Academic scores.
  • Status consists of Not Qualified and Qualified.
  • What we will classify is Name = See, Mathematics Score = 81, Indonesian Score = 86, English Score = 79, Science Score = 93 and Non Academic Score = 87, Status = ?
 Calculation (formula to be used) :


  • 79 is Alan's Math score
  • 81 is See's Math score
  • 88 is Alan's Indonesian score
  • 86 is See's Indonesian score
  • 72 is Alan's British value
  • 79 is See's British value
  • 92 is Alan's Science score
  • 93 is See's Science score
  • 97 is Alan's Non-Academic score
  • 87 is See's Non-Academic score
  • Then do the same calculations on data belonging to Dani, Rey and so on.
  • 1/3 is the power for Minkowsky's formula
 Then the calculation will be obtained as follows :


After that, do the ranking from the smallest to the largest value, the results obtained are as follows :


After getting the ranking, we can ensure that on behalf of See is eligible to receive a Scholarship or Not Eligible to receive a Scholarship.


Explanation :
  • If using K = 1 then the result is not eligible because Moon the result is not eligible.
  • If using K=3 then the result is not eligible because Moon, Eks and Alan the results are not eligible (3 are not eligible).
  • If using K=5, the result is not eligible because Dani is eligible, while Moon, Eks, Alan and Zet are not eligible (full requirements totaling 1 and not fulfilling requirements totaling 4).
So the final result See does not meet the requirements


Notes :
  • The value of K is independent (try to have an odd number so it doesn't confuse us when there are the same number of voting results).

Rabu, 23 Agustus 2023

Convert Decimal to Binary

By using the calculation formula for converting decimal numbers to other bases, we can do the following.

Example :

6710 = ……2 ?

Suppose we are going to convert 67 base ten (decimal) to base 2 (binary).

1.     First we divide 67 by 2, we get the integer quotient is 33 with the remainder 1, or in other words 67 = 2*33 + 1

2.     Then we divide the integer quotient (33) by 2 again, 33/2 = 16, the remainder is 1.

3.     Then we repeat again, 16/2 = 8, the remainder is 0.

4.     Repeat these steps again until the integer quotient equals 0. After that, write down the remainder of the quotient starting from the bottom up.

Thus we will get that 6710 = 10000112.

Minggu, 20 Agustus 2023

Calculation of K-Nearest Neighbor with Manhattan Distance (5 Criteria)

In this post, I will discuss the calculation of K-Nearest Neighbor with Manhattan Distance using 5 criteria.

The classification that will be discussed is the Classification of Scholarship Recipients.

The data we will use is :

  • Consists of 10 data
  • Consists of 5 criteria
  • K = 5



Information :

  • What will be categorized consists of Mathematics scores, Indonesian B scores, English B grades, Science scores and Non-Academic scores.
  • Status consists of Not Qualified and Qualified.
  • What we will classify is Name = See, Mathematics Score = 81, Indonesian Score = 86, English Score = 79, Science Score = 93 and Non Academic Score = 87, Status = ?

 Calculation (formula to be used):



  • 79 is Alan's Math score
  • 81 is See's Math score
  • 88 is Alan's Indonesian score
  • 86 is See's Indonesian score
  • 72 is Alan's British value
  • 79 is See's British value
  • 92 is Alan's Science score
  • 93 is See's Science score
  • 97 is Alan's Non-Academic score
  • 87 is See's Non-Academic score
  • Then do the same calculations on data belonging to Dani, Rey and so on.

 Then the calculation will be obtained as follows :



After that, do the ranking from the smallest to the largest value, the results obtained are as follows :



After getting the ranking, we can ensure that on behalf of See is eligible to receive a Scholarship or Not Eligible to receive a Scholarship.



Explanation :

  • If using K=1 then the result is eligible because Dani the result is eligible.
  • If using K=3 then the result is not eligible because Dani's result is eligible, while Alan and Cee's results are not eligible (fulfilling the requirements is 1 and not fulfilling the requirements is 2).
  • If using K=5, the result is not eligible because Dani and Rey are eligible, while Alan, Cee and Eks are not eligible (2 meet the requirements and 3 do not meet the requirements).

So the final result See does not meet the requirements.



Notes :

  • The value of K is independent (try to have an odd number so it doesn't confuse us when there are the same number of voting results).

Kamis, 17 Agustus 2023

Konversi Desimal ke Biner

Dengan menggunakan rumus perhitungan konversi bilangan desimal ke basis lainnya kita bisa lakukan sebagai berikut.

Contoh :

6710 = ……2 ?

Misalkan kita akan melakukan konversi 67 basis sepuluh (desimal) ke dalam basis 2 (biner).
  1. Pertama-tama kita bagi 67 dengan 2, didapat bilangan bulat hasil bagi adalah 33 dengan sisa hasil bagi adalah 1, atau dengan kata lain 67 = 2*33 + 1
  2. Selanjutnya bilangan bulat hasil bagi tersebut (33) kita bagi dengan 2 lagi, 33/2 = 16, sisa hasil bagi
  3. Kemudian kita ulangi lagi, 16/2 = 8, sisa hasil bagi 0.
  4. Ulangi lagi langkah tersebut sampai bilangan bulat hasil bagi sama dengan 0. Setelah itu tulis sisa hasil bagi mulai dari bawah ke atas.
  5. Dengan demikian kita akan mendapatkan bahwa 6710 = 10000112.

Minggu, 13 Agustus 2023

Calculation of K-Nearest Neighbor with Euclidean Distance (5 Criteria)

In this post, I will discuss the calculation of K-Nearest Neighbor with Euclidean Distance using 5 criteria.

The classification that will be discussed is the Classification of Scholarship Recipients.

The data we will use is:
  • Consists of 10 data
  • Consists of 5 criteria
  • K = 5


Information :
  • What will be categorized consists of Mathematics scores, Indonesian scores, English scores, Science scores and Non-Academic scores.
  • Status consists of Not Qualified and Qualified.
  • What we will classify is Name = See, Mathematics Score = 81, Indonesian Score = 86, English Score = 79, Science Score = 93 and Non Academic Score = 87, Status = ?

Calculation (formula to be used) :


  • 79 is Alan's Math score
  • 81 is See's Math score
  • 88 is Alan's Indonesian score
  • 86 is See's Indonesian score
  • 72 is Alan's British value
  • 79 is See's British value
  • 92 is Alan's Science score
  • 93 is See's Science score
  • 97 is Alan's Non-Academic score
  • 87 is See's Non-Academic score
  • Then do the same calculations on data belonging to Dani, Rey and so on.

Then the calculation will be obtained as follows :


After that, do the ranking from the smallest to the largest value, the results obtained are as follows :


After getting the ranking, we can ensure that on behalf of See is eligible to receive a Scholarship or Not Eligible to receive a Scholarship.


Explanation :
  • If using K=1 then the result is Qualified because Dani's result is Qualified.
  • If using K=3 then the result is Not Qualified because Dani's result is Qualified, while Cee and Moon's result is Not Qualified (Qualified is 1 and Unqualified is 2).
  • If you use K=5 then the result is Not Qualified because Dani and Rey are Qualified, while Cee, Tet and Alan are Not Eligible (2 Qualified and 3 Unqualified).
So that the final result of See Not Qualifying.


Notes :
  • The value of K is independent (try to have an odd number so it doesn't confuse us when there are the same number of voting results).

Kamis, 10 Agustus 2023

IP Address Assignment

IP addresses are assigned to hosts either dynamically as they join the network, or persistently by host hardware or software configuration. Persistent configuration is also known as using a static IP address. Conversely, when a computer's IP address is assigned each time it is restarted, this is known as using a dynamic IP address . 

Dynamic IP addresses are assigned by the network using the Dynamic Host Configuration Protocol (DHCP). DHCP is the most frequently used technology for assigning addresses. This avoids the administrative burden of assigning specific static addresses to each device on the network. It also allows devices to share a limited address space on a network if only a few of them are online at any given time. Usually, dynamic IP configuration is enabled by default in modern desktop operating systems. 

Addresses assigned with DHCP are associated with leases and usually have an expiration date. If the lease is not renewed by the host before it expires, the address may be assigned to another device. Some DHCP implementations attempt to reassign the same IP address to a host, based on its MAC address, each time it joins a network. Network owners can configure DHCP by allocating specific IP addresses based on MAC addresses. 

DHCP isn't the only technology used to dynamically assign IP addresses. Bootstrap Protocol is a protocol and predecessor similar to DHCP. Dialup and some broadband networks use the dynamic addressing feature of the Point-to-Point Protocol. 

Computers and equipment used for network infrastructure, such as routers and mail servers, are typically configured with static addresses. 

In the absence or failure of static or dynamic address configuration, the operating system can assign link-local addresses to hosts using stateless address autoconfiguration.

Selasa, 08 Agustus 2023

Calculation of K-Nearest Neighbor With Minkowsky Distance

In this post, I will discuss the calculation of K-Nearest Neighbor with Minkowsky Distance.

The classification that will be discussed is the Classification of Scholarship Recipients.

The data we will use is:

  • Consists of 10 data
  • Consists of 2 criteria
  • K = 5
  • r Minkowsky = 4


Information :
  • Which will be categorized consists of Non-Academic values ​​and Academic values.
  • Status consists of Not Qualified and Qualified.
  • What we will classify is Name = See, Non-Academic Value = 81 and Academic Value = 86, Status = ?
 
Calculation (formula to be used) :


  • 79 is Alan's Non-Academic score
  • 81 is See's Non-Academic score
  • 97 is Alan's Academic score
  • 86 is See's Academic score
  • 1/4 is a power value, because r = 4
  • Then do the same calculations on data belonging to Dani, Rey and so on.

Then the calculation will be obtained as follows :


After that, do the ranking from the smallest to the largest value, the results obtained are as follows :


After getting the ranking, we can ensure that on behalf of See is eligible to receive a Scholarship or Not Eligible to receive a Scholarship.


Explanation :
  • If using K=1 then the result is Not Qualified because Moon the result is Not Qualified.
  • If using K=3 then the result is Not Qualified because Dani's result is Qualified, while Moon and Tet the result is Not Qualified (Qualified is 1 and Unqualified is 2).
  • If using K=5 then the result is Not Qualified because Dani's result is Qualified, while Moon, Tet, Cee and Jo the result is Not Qualified (Qualified is 1 and Unqualified is 4).

So that the final result of See Not Qualifying


Notes :
  • The value of K is independent (try to have an odd number so it doesn't confuse us when there are the same number of voting results).

Minggu, 06 Agustus 2023

Penugasan Alamat IP

Alamat IP ditetapkan untuk host baik secara dinamis saat mereka bergabung dengan jaringan, atau secara terus-menerus dengan konfigurasi perangkat keras atau perangkat lunak host. Konfigurasi persisten juga dikenal sebagai menggunakan alamat IP statis. Sebaliknya, ketika alamat IP komputer ditetapkan setiap kali restart, ini dikenal dengan menggunakan alamat IP dinamis. 

Alamat IP dinamis ditetapkan oleh jaringan menggunakan Dynamic Host Configuration Protocol (DHCP). DHCP adalah teknologi yang paling sering digunakan untuk menetapkan alamat. Ini menghindari beban administrasi menetapkan alamat statis spesifik untuk setiap perangkat di jaringan. Ini juga memungkinkan perangkat untuk berbagi ruang alamat terbatas pada jaringan jika hanya beberapa dari mereka yang online pada waktu tertentu. Biasanya, konfigurasi IP dinamis diaktifkan secara default di sistem operasi desktop modern. 

Alamat yang ditetapkan dengan DHCP dikaitkan dengan sewa dan biasanya memiliki masa kedaluwarsa. Jika sewa tidak diperpanjang oleh tuan rumah sebelum kedaluwarsa, alamat dapat ditugaskan ke perangkat lain. Beberapa implementasi DHCP mencoba untuk menetapkan kembali alamat IP yang sama ke host, berdasarkan alamat MAC-nya, setiap kali bergabung dengan jaringan. Pemilik jaringan dapat mengkonfigurasi DHCP dengan mengalokasikan alamat IP tertentu berdasarkan alamat MAC. 

DHCP bukan satu-satunya teknologi yang digunakan untuk menetapkan alamat IP secara dinamis. Bootstrap Protocol adalah protokol dan pendahulu yang mirip dengan DHCP. Dialup dan beberapa jaringan broadband menggunakan fitur alamat dinamis dari Point-to-Point Protocol. 

Komputer dan peralatan yang digunakan untuk infrastruktur jaringan, seperti router dan server surat, biasanya dikonfigurasikan dengan pengalamatan statis. 

            Dengan tidak adanya atau kegagalan konfigurasi alamat statis atau dinamis, sistem operasi dapat menetapkan alamat tautan-lokal ke host menggunakan konfigurasi otomatis alamat stateless. 

Sabtu, 05 Agustus 2023

Calculation of K-Nearest Neighbor With Euclidean Distance

In this post, I will discuss the calculation of K-Nearest Neighbor with Euclidean Distance.

The classification that will be discussed is the Classification of Scholarship Recipients.

The data we will use is:
  • Consists of 10 data
  • Consists of 2 criteria
  • K = 5



Information :
  • Which will be categorized consists of Non-Academic values ​​and Academic values.
  • Status consists of TMS (Not Qualified) and MS (Qualified).
  • What we will classify is Name = See, Non-Academic Value = 81 and Academic Value = 86, Status = ?

Calculation (formula to be used) :


  • 79 is Alan's Non-Academic score
  • 81 is See's Non-Academic score
  • 97 is Alan's Academic score
  • 86 is See's Academic score
  • Then do the same calculations on data belonging to Dani, Rey and so on.

Then the calculation will be obtained as follows :



After that, do the ranking from the smallest to the largest value, the results obtained are as follows :



After getting the ranking, we can ensure that on behalf of See is eligible to receive a Scholarship or Not Eligible to receive a Scholarship.



Explanation :
  • If using K = 1 then the result is eligible because Dani the result is eligible.
  • If using K=3 then the result is not eligible because Dani's result is eligible, while Cee and Moon's result is not eligible (fulfilling the requirements is 1 and not fulfilling the requirements is 2).
  • If using K=5, the result is not eligible because Dani and Eks are eligible, while Cee, Moon and Tet are ineligible (2 met the requirements and 3 did not fulfill the requirements).
So the final result See does not meet the requirements.



Notes :
  • The value of K is independent (try to have an odd number so it doesn't confuse us when there are the same number of voting results).

Rabu, 02 Agustus 2023

Calculation of K-Nearest Neighbor With Manhattan Distance

 In this post, I will discuss the calculation of K-Nearest Neighbor with Manhattan Distance.

The classification that will be discussed is the Classification of Scholarship Recipients.

The data we will use is:

Consists of 10 data

Consists of 2 criteria

K = 5





Information :

  • Which will be categorized consists of Non-Academic values ​​and Academic values.
  • Status consists of TMS (Not Qualified) and MS (Qualified).
  • What we will classify is Name = See, Non-Academic Value = 81 and Academic Value = 86, Status = ?

 Calculation (formula to be used) :



  • 79 is Alan's Non-Academic score
  • 81 is See's Non-Academic score
  • 97 is Alan's Academic score
  • 86 is See's Academic score
  • Then do the same calculations on data belonging to Dani, Rey and so on.
  • Keep in mind, for Manhattan the final result must be absolute value.

 


Then the calculation will be obtained as follows :



After that, do the ranking from the smallest to the largest value, the results obtained are as follows :



After getting the ranking, we can ensure that on behalf of See is eligible to receive a Scholarship or Not Eligible to receive a Scholarship.



Explanation :

  • If using K=1 then the result is MS because Dani the result is MS.
  • If using K=3, the result is TMS because Dani's result is MS, while Cee and Moon's result is TMS (1 MS and 2 TMS).
  • If using K=5 then the result is TMS because Dani's result is MS, while Cee, Moon, Jo and Alan the result is TMS (1 MS and 4 TMS).

So that the final result See TMS



Notes :

  • The value of K is independent (try to have an odd number so it doesn't confuse us when there are the same number of voting results).