Data Set (Distance (minkowsky))

In this post, I will give an example of calculating distances using Minkowski distance.

I have 2 pieces of data.

This data consists of X data and Y data.

Data X consists of = 5, 3, 1, 0, 1

Data Y consists of = 1, 0, 3, 4, 2

r = 4

We will calculate the data using the minkowski distance.

The formula we will use is :

For Minkowski's calculations, there is a power that is r, which has a value of 1/r

To perform the following calculations :

The explanation is :

• 7 = is the first number of data X
• 1 = is the first number of data Y
• So the formula is X's first data minus Y's first data and so on

So the next calculation is like this :

The explanation is:

• 1/r is the power to which the last calculation will be performed
• r here is worth 4 (can be any value)

So, the distance between the two data using the Minkowski distance is 0.5

Sub network

    IP networks can be divided into subnetworks in IPv4 and IPv6. For this purpose, the recognized IP address consists of two parts: the network prefix in the high-order bits and the remaining bits called the remainder field, the host identifier , or interface identifier (IPv6), is used for the numbering of hosts in the network. The subnet mask or CIDR notation determines how an IP address is divided into network and host parts.

    The term subnet mask is only used in IPv4. But both versions of IP use the CIDR concept and notation. In this case, the IP address is followed by a slash and the number (in decimal) of the bits used for the network portion, also called the routing prefix . For example, an IPv4 address and subnet mask could be 192.0.2.1 and 255.255.255.0 respectively . The CIDR notation for the same IP address and subnet is 192.0.2.1/24 , because the first 24 bits of an IP address indicate the network and subnet.

Data Set (Calculating Distance With Manhattan) Using Excel

How to calculate the distance to Manhattan using Excel is as follows:

The data that we will use is

The formula we will use is as follows:

• =ABS((B3-C3)+(B4-C4)+(B5-C5)+(B6-C6)+(B7-C7))
• 1

The result should be -1, because for the calculation of the Manhattan distance it must have an absolute value. Then the value -1 has a house of 1

Explanation :

• ABS is a formula in excel for absolute numbers
• B3, C3 and so on are columns of numbers in excel

Sub jaringan

    Jaringan IP dapat dibagi menjadi beberapa subnetwork di IPv4 dan IPv6. Untuk tujuan ini, alamat IP diakui terdiri dari dua bagian: awalan jaringan dalam bit orde tinggi dan bit yang tersisa disebut bidang sisanya, pengidentifikasi host, atau pengidentifikasi antarmuka (IPv6), digunakan untuk penomoran host dalam jaringan. Subnet mask atau notasi CIDR menentukan bagaimana alamat IP dibagi menjadi bagian-bagian jaringan dan host.

    Istilah subnet mask hanya digunakan dalam IPv4. Namun kedua versi IP menggunakan konsep dan notasi CIDR. Dalam hal ini, alamat IP diikuti oleh garis miring dan nomor (dalam desimal) bit yang digunakan untuk bagian jaringan, juga disebut routing prefix. Misalnya, alamat IPv4 dan subnet mask-nya masing-masing bisa 192.0.2.1 dan 255.255.255.0. Notasi CIDR untuk alamat IP dan subnet yang sama adalah 192.0.2.1/24, karena 24 bit pertama dari alamat IP menunjukkan jaringan dan subnet.

Data Set (Comparison of Distance to manhattan)

In this post, I will give an example of calculating distance comparisons using the Manhattan distance.

I have 3 pieces of data.

This data consists of X data, Y data and Z data.

Data X consists of = 3, 0, 2, 5, 0

Y data consists of = 0, 5, 1, 1, 3

Data Z consists of = 1, 4, 4, 3, 1

From the data above, we will look for a comparison of the distance between Data X to Data Y, Data Y to Data Z and Data Z to Data X

Distance of Data X to Data Y

So, the Distance of Data X to Data Y is 0

Distance of Data Y to Data Z

So, the Distance of Data Y to Data Z is 3

Distance of Data Z to Data X

So, the Distance of Data Z to Data X is 3

From the results of the three distances found as follows :

From the data above, it is obtained that the distance from Data X to Data Y is the closest distance to the value 0

IP Address Function

    An IP address serves two principal functions: it identifies the host, or more specifically its network interface, and it provides the location of the host in the network, and thus the capability of establishing a path to that host. Its role has been characterized as follows: "A name indicates what we seek. An address indicates where it is. A route indicates how to get there." The header of each IP packet contains the IP address of the sending host and that of the destination host.

Data Set (Distance (manhattan))

Data Set (Distance (manhattan))

In this post I will give an example of calculating the distance using the manhattan distance.

I have 2 pieces of data.

This data consists of X data and Y data.

Data X consists of = 5, 3, 1, 0, 1

Data Y consists of = 1, 0, 3, 4, 2

We will calculate the data using the Manhattan distance.

The formula we will use is :

To perform the following calculations :

The explanation is:

• 5 = is the first number of data X
• 1 = is the first number of data Y
• So the formula is X's first data minus Y's first data and so on

So the next calculation is like this:

So, the distance between the two data using the manhattan distance is 0

Notes :

• Calculating the distance using Manhattan, the final result must be absolute
• If the final result is -1, then the absolute value is 1

Fungsi IP address

Fungsi alamat IP melayani dua fungsi utama. Ini mengidentifikasi host, atau lebih khusus antarmuka jaringannya, dan menyediakan lokasi host di jaringan, dan dengan demikian kemampuan membangun jalur ke host tersebut. Perannya telah ditandai sebagai berikut: "Sebuah nama menunjukkan apa yang kita cari. Alamat menunjukkan di mana tempatnya. Rute menunjukkan bagaimana menuju ke sana." Header setiap paket IP berisi alamat IP dari host pengirim, dan host tujuan.

Data Sets (Calculating Distances With Euclidean) Using Excel

Data Sets (Calculating Distances With Euclidean) Using Excel

How to calculate the distance with Euclidean using Excel is as follows:

The data that we will use is

The formula we will use is as follows:

• =SQRT((B3-C3)^2+(B4-C4)^2+(B5-C5)^2+(B6-C6)^2+(B7-C7)^2)
• = 6.782329983

Explanation :

• SQRT is a formula in excel for roots
• B3, C3 and so on are columns of numbers in excel
• ^ is a power formula in excel

IP address

IP address

    An Internet Protocol address (IP address) is a numerical label such as 192.0.2.1 that is connected to a computer network that uses the Internet Protocol for communication. An IP address serves two main functions: network interface identification and location addressing.

    Internet Protocol version 4 (IPv4) defines an IP address as a 32-bit number. However, because of the growth of the Internet and the depletion of available IPv4 addresses, a new version of IP (IPv6), using 128 bits for the IP address, was standardized in 1998. IPv6 deployment has been ongoing since the mid-2000s. 

    IP addresses are written and displayed in human-readable notations, such as 192.0.2.1 in IPv4, and 2001:db8:0:1234:0:567:8:1 in IPv6. The size of the routing prefix of the address is designated in CIDR notation by suffixing the address with the number of significant bits, e.g., 192.0.2.1/24, which is equivalent to the historically used subnet mask 255.255.255.0. 

    The IP address space is managed globally by the Internet Assigned Numbers Authority (IANA), and by five regional Internet registries (RIRs) responsible in their designated territories for assignment to local Internet registries, such as Internet service providers (ISPs), and other end users. IPv4 addresses were distributed by IANA to the RIRs in blocks of approximately 16.8 million addresses each, but have been exhausted at the IANA level since 2011. Only one of the RIRs still has a supply for local assignments in Africa. Some IPv4 addresses are reserved for private networks and are not globally unique. 

    Network administrators assign an IP address to each device connected to a network. Such assignments may be on a static (fixed or permanent) or dynamic basis, depending on network practices and software features.

Data Set (Comparison of Distance to Euclidean)

Data Set (Comparison of Distance to Euclidean)

In this post, I will give an example of calculating distance comparisons using the Euclidean distance.

I have 3 pieces of data.

This data consists of X data, Y data and Z data. 

Data X consists of = 3, 0, 2, 5, 0 

Y data consists of = 0, 5, 1, 1, 3 

Data Z consists of = 1, 4, 4, 3, 1

From the data above, we will look for a comparison of the distance between Data X to Data Y, Data Y to Data Z and Data Z to Data X

Distance of Data X to Data Y

So, the distance from Data X to Data Y is 7.7459666924

Distance of Data Y to Data Z

So, the Distance of Data Y to Data Z is 4.3588989435

Distance of Data Z to Data X

So, the Distance of Data Z to Data X is 5.3851648071

From the results of the three distances found as follows:

From the data above, the distance obtained from Data Y to Data Z is the closest distance with a value of 4.3588989435