Assignment 6: Clustering & Eample

CLUSTERING

Clustering Analysis
Clustering analysis is finding similarities between data according to the characteristics found in the data and grouping similar data objects into clusters.

Two Categories of Clustering Analysis Methods:
1. Hierarchical Cluster Analysis Methods
a. Agglomerative Methods
In Agglomerative methods, all methods start in separate clusters till slowly similar objects are combined and this process is repeated till all objects are in a single cluster. Finally, the optimum number of clusters is chosen from among all options.

b. Divisive Methods
In Divisive Methods, all objects the same cluster and the reverse of the agglomerative method is used.

2. Non-hierarchical Cluster Analysis Methods
(known as k-means clustering methods)
K-means used when large data sets are involved. Further, these provide the flexibility of moving a subject from one cluster to another.

An example in daily life:

Clusters play an important role in "human development". For example, all natural objects are basically classified into groups: animals, plants, minerals. According to the biological taxonomy, all animals are grouped into categories of the kingdom, phylum, class, order, family, genus, species from the general to the specific. There are animals named tigers, lions, wolves, dogs, horses, sheep, cats, mice etc. 

Big Data Assignment 5: Modeller, Simulator, Optimizer

Modeller, Simulator, Optimizer

A. Definition

1. Modeller
• A modeller is a person who represents a construction and work of several systems and makes approach the estimates of actual systems.
• A model that makes by a modeller will be better if it is simple and real because it will make it easier to understand.
2. Simulator
• A simulator is a device which artificially creates to enables the operators to represent under test conditions phenomena likely to occur in actual performance.
• A simulator is usually used in training people such as pilots, and astronauts. a simulator also can use in car racing games.
3. Optimizer
• An optimizer is a program that uses linear programming to optimize a process.
• An optimizer will help to show an optimum process.

B. Example

In Indonesia, especially in Batu, Malang have Museum Angkut. Museum Angkut displays various transportation (land, sea and air transportation). Not only that there is a simulation vehicle for visitors. Simulation that available in there are flight and race car simulation. Beside to attract visitors, the simulation provides an opportunity to feel how the drivers drive a car and how the pilot operates the plane until it lands. This is a picture of race care simulation in Museum Angkut:

In addition car simulation very useful to improve driving training, train someone to be able to drive a car and conditions where the driver must be careful, ensure that he remains safe in potentially dangerous conditions in various choices of road conditions (Night mode, Fog mode and Highway experience). Driving simulators can also be used for exams to get a Driving License.

And flight simulator useful when apply the tools to simulate control or function like real aeroplanes, as a pilot training vehicle in terms of pilot education about increasing agility in "operating" the aircraft used later, and pilot readiness will be more tested and honed in what circumstances the pilot will make decisions in the best, ordinary or worst situations.