Computational Thinking or what can be called Computational Thought is a problem solving process that includes a number of characteristics and dispositions. Computational Thinking is very important for the development of a computer application, but can also be used to support problem solving in every science, including humanities, mathematics, and science. One element of Computational Thinking is Design Algorithm, or what can be called algorithmic thinking.

The Design algorithm is a special method for creating mathematical processes in the problem solving process. The Design Algorithm is identified and incorporated into many operating research solution theories, as well as dynamic programming. Techniques for designing and implementing algorithmic designs are algorithmic design patterns, such as template pattern patterns and decorator patterns, as well as the use of data structures. Some uses of algorithms today can be found in internet search processes such as web crawling, packet routing and caching.

Algorithm analysis is done with the main goal so that we can make the right decision in choosing an algorithm to find and determine a solution. For example, we all learn algorithms to do multiplication at school. If we follow the rules and steps taught, we can actually get answers to multiplication problems. Once we have an algorithmic rationale we don't need to think about how to do multiplication from zero every time we are faced with a new problem.

As one of the foundations of computer science, algorithms are very important to be mastered by people, from researchers to practitioners, so that it may need to be learned by ordinary people in the world of computer science. Of course the mastery of algorithms is not enough just to get to the stage of knowing and using the right algorithm to solve the problem. A person who understands computer science must also be able to design and develop an algorithm based on the problems encountered. It is a good idea to learn fundamentally about the design and development of algorithms, so that we can not only use existing algorithms, but also design and develop algorithms in accordance with the problems that will be solved.

In defining algorithm analysis, we must be able to clearly define three main things, namely:

• Problem, which is a problem that an algorithm wants to solve.
• Input, which is an example of data or filtered state, can be variables to find a way out of a problem ...
• Output, which is the final form of data or state after the algorithm is implemented to input. Output is the ideal result desired and is considered to have solved the problem or found the right solution.