Béda révisi "Algoritma"

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'''Algoritma''' nyaéta susunan paréntah, nu jumlahna kawates, pikeun ngolah sababaraha paréntah nu, sakumpulan data asupanana, bakal ngahasilkeun sarupaning bentuk ahir nu bisa dipikawanoh; sabalikna ti [[heuristik]]. Konsép algoritma mindeng digambarkeun ku conto hiji [[resép]], sanajan loba algoritma kacida ruwetna; algoritma sering miboga léngkah-léngkah anu malikan ([[iterasi]]) atawa merlukeun kaputusan (saperti [[logika Boolean|logika]] atawa [[kahenteusaruaan|perbandingan]]) nepi ka tugas diréngsékeunnana.
Different algorithms may complete the same task with a different set of instructions in more or less time, space, or effort than others. For example, given two different recipes for making potato salad, one may have ''peel the potato'' before ''boil the potato'' while the other presents the steps in the reverse order, yet they both call for these steps to be repeated for all potatoes and end when the potato salad is ready to be eaten. <!-- poor example .. who would boil each potato separately? and making a salad in general requires no cooking ... -->
Correctly performing an algorithm will not solve a problem if the algorithm is flawed or not appropriate to the problem. For example, performing the potato salad algorithm will fail if there are no potatoes present, even if all the motions of preparing the salad are performed as if the potatoes were there.
In some countries, such as the USA, some algorithms can effectively be [[Patent|patented]] if an embodiment is possible (for example, a multiplication algorithm embodied in the arithmetic unit of a microprocessor).
== Algoritma nu dirumuskeun ==
specified task, such as calculating employees’ paychecks or printing students’ report cards. Thus, an algorithm can be considered to be any sequence of operations which can be performed by a [[Turing-complete]] system.
Typically, when an algorithm is associated with processing information, data is read from an input source or device, written to an output sink or device, and/or stored for further use. Stored data is regarded as part of the [[internal state]] of the entity performing the algorithm.
For any such computational process, the algorithm must be rigorously defined: specified in the way it applies in all possible circumstances that could arise. That is, any conditional steps must be systematically dealt with, case-by-case; the criteria for each case must be clear (and computable).
An '''algorithm''' is a method or procedure for carrying out a task (such as solving a problem in [[mathematics]], finding the freshest produce in a supermarket, or manipulating [[information]] in general).
Algorithms are sometimes implemented as [[computer program]]s but are more often implemented by other means, such as in a biological neural network (for example, the human brain implementing [[arithmetic]] or an insect relocating food), or in [[electric circuit]]s or in a mechanical device.
The [[analysis of algorithms|analysis and study of algorithms]] is one discipline of [[computer science]], and is often practiced abstractly (without the use of a specific [[programming language]] or other implementation). In this sense, it resembles other mathematical disciplines in that the analysis focuses on the underlying principles of the algorithm, and not on any particular implementation. One way to embody (or sometimes ''codify'') an algorithm is the writing of [[pseudocode]].
Some writers restrict the definition of ''algorithm'' to procedures that eventually finish. Others include procedures that could run forever without stopping, arguing that some entity may be required to carry out such permanent tasks. In the latter case, success can no longer be defined in terms of halting with a meaningful output. Instead, terms of success that allow for unbounded output sequences must be defined. For example, an algorithm that verifies if there are more zeros than ones in an infinite random binary sequence must run forever to be effective. If it is implemented correctly, however, the algorithm's output will be useful: for as long as it examines the sequence, the algorithm will give a positive response while the number of examined zeros outnumber the ones, and a negative response otherwise. Success for this algorithm could then be defined as eventually outputting only positive responses if there are actually more zeros than ones in the sequence, and in any other case outputting any mixture of positive and negative responses.
== Conto ==
Notes on notation:
* ''='' as used here indicates assignment. That is, the value on the right-hand side of the expression is assigned to the container (or variable) on the left-hand side of the expression.
* ''List[counter]'' as used here indicates the counter<sup>th</sup> element of the list. For example: if the value of ''counter'' is 5, then ''List[counter]'' refers to the 5<sup>th</sup> element of the list.
* ''<='' as used here indicates 'less than or equal to'
Note also the algorithm assumes that the list contains at least one number. It will fail when presented an empty list.
Kecap ''algoritma'' comes ultimately from the name of the [[9th century|9<sup>th</sup>-century]] mathematician [[al-Khwarizmi|Abu Abdullah Muhammad bin Musa al-Khwarizmi]]. The word ''[[algorism]]'' originally referred only to the rules of performing [[arithmetic]] using [[Arabic numerals]] but evolved into ''algorithm'' by the [[18th century]]. The word has now evolved to include all definite procedures for solving problems or performing tasks.
The first case of an algorithm written for a [[computer]] was [[Ada Lovelace|Ada Byron]]'s [[Ada Byron's notes on the analytical engine|notes on the analytical engine]] written in [[1842]], for which she is considered by many to be the world's first [[programmer]]. However, since [[Charles Babbage]] never completed his [[analytical engine]] the algorithm was never implemented on it.
The lack of [[mathematical rigor]] in the "well-defined procedure" definition of algorithms posed some difficulties for mathematicians and [[logic]]ians of the [[19th century|19th]] and early [[20th century|20th centuries]]. This problem was largely solved with the description of the [[Turing machine]], an abstract model of a [[computer]] formulated by [[Alan Turing]], and the demonstration that every method yet found for describing "well-defined procedures" advanced by other mathematicians could be emulated on a Turing machine (a statement known as the [[Church-Turing thesis]]).
Nowadays, a formal criterion for an algorithm is that it is a procedure that can be implemented on a completely-specified Turing machine or one of the equivalent [[formalism]]s. Turing's initial interest was in the [[halting problem]]: deciding when an algorithm describes a terminating procedure. In practical terms [[computational complexity theory]] matters more: it includes the puzzling problem of the algorithms called [[NP-complete]], which are generally presumed to take more than polynomial time.
* The probabilistic and heuristic paradigm. Algorithms belonging to this class fit the definition of an algorithm more loosely. [[Probabilistic algorithm]]s are those that make some choices randomly (or pseudo-randomly); for some problems, it can in fact be proved that the fastest solutions must involve some randomness. [[Genetic algorithm]]s attempt to find solutions to problems by mimicking biological [[evolution]]ary processes, with a cycle of random mutations yielding successive generations of 'solutions'. Thus, they emulate reproduction and "survival of the fittest". In [[genetic programming]], this approach is extended to algorithms, by regarding the algorithm itself as a 'solution' to a problem. Also there are [[heuristic]] algorithms, whose general purpose is not to find a final solution, but an approximate solution where the time or resources to find a perfect solution are not practical. An example of this would be [[simulated annealing]] algorithms, a class of [[heuristic]] [[probabilistic algorithm]]s that vary the solution of a problem by a random amount. The name 'simulated annealing' alludes to the metallurgic term meaning the heating and cooling of metal to achieve freedom from defects. The purpose of the random variance is to find close to globally optimal solutions rather than simply locally optimal ones, the idea being that the random element will be decreased as the algorithm settles down to a solution.
Another way to classify algorithms is by implementation. A [[recursive algorithm]] is one that invokes (makes reference to) itself repeatedly until a certain condition matches, which is a method common to [[functional programming]]. Algorithms are usually discussed with the assumption that computers execute one instruction of an algorithm at a time. Those computers are sometimes called serial computers. An algorithm designed for such an environment is called a serial algorithm, as opposed to [[parallel algorithm]]s, which take advantage of computer architectures where several processors can work on a problem at the same time. The various heuristic algorithm would probably also fall into this category, as their name (e.g. a genetic algorithm) describes its implementation.
A [[list of algorithms]] discussed in Wikipedia is available.
== Tempo ogé ==
* [[Algorism]]
* [[Bulletproof algorithm]]s
* [[Numerical analysis]]
* [[Cryptography|Cryptographic algorithms]]
* [[Sort algorithm]]s
* [[Search algorithm]]s
* [[Merge algorithm]]s
* [[String algorithms]]
* [[List of algorithms]]
* [[Timeline of algorithms]]
* [[Struktur data]]
* [[Genetic Algorithm]]s
* [[Randomised algorithm]]s
* [[Computability logic]]
== Sumber séjén ==
* [[Donald E Knuth]]: ''[[The Art of Computer Programming]]'', Vol 1–3, Addison Wesley 1998. Widely held as a definitive reference. ISBN 0-201-48541-9.
* [[List of important publications in computer science#Algorithms|Important algorithm-related publications]]
* [http://www.nist.gov/dads/ Dictionary of Algorithms and Data Structures]. "This is a dictionary of algorithms, algorithmic techniques, data structures, archetypical problems, and related definitions."
* [http://www.nr.com Numerical Recipes]
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