Béda révisi "Algoritma"

5 bita ditambahkeun ,  5 tahun yang lalu
m
Ngarapihkeun éjahan, replaced: nyaeta → nyaéta (2), make → maké (3), rea → réa (4), ea → éa (26), eo → éo, kabeh → kabéh using AWB
m (Bot: Ngaganti Abu_Abdullah_Muhammad_bin_Musa_al-Khwarizmi.jpg ku 1983_CPA_5426.jpg)
m (Ngarapihkeun éjahan, replaced: nyaeta → nyaéta (2), make → maké (3), rea → réa (4), ea → éa (26), eo → éo, kabeh → kabéh using AWB)
'''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.
{{Tarjamahkeun|Inggris}}
sababaraha alogaritma bisa anggeus ku pagaweanpagawéan nu sarua makemaké susunan parentah nu beda 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 repeatedrepéated for all potatoes and end when the potato salad is readyréady to be eatenéaten. <!-- 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|patentedpatent]]ed 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 readréad 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 dealtdéalt with, case-by-case; the criteria for eachéach case must be clearcléar (and computable).
 
Because an algorithm is a precise list of precise steps, the order of computation will almost always be critical to the functioning of the algorithm. Instructions are usually assumed to be listed explicitly, and are described as starting 'from the top' and going 'down to the bottom', an ideaidéa that is described more formally by ''[[control flow|flow of control]]''.
 
So far, this discussion of the formalisation of an algorithm has assumed the premises of [[imperative programming]]. This is the most common conception, and it attempts to describe a task in discrete, 'mechanical' meansméans. Unique to this conception of formalized algorithms is the [[assignment operation]], setting the value of a variable. It derives from the intuition of 'memory' as a scratchpad. There is an example below of such an assignment.
 
See [[functional programming]] and [[logic programming]] for alternate conceptions of what constitutes an algorithm.
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 meansméans, 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 meaningfulméaningful output. InsteadInstéad, 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 ==
Di dieu aya conto sederhana dina algoritma.
 
Bayangkeun anjeun mibanda wilangan random dina daptar nu teu kasortir. Tujuan ahirna keur manggihkeun wilangan panggedena tina etaéta daptar. Lengkah mimiti nyaetanyaéta kudu nempo kana sakabehsakabéh nilai nu aya dina deret. Lengkah saterusna nyaetanyaéta nempo kana etaéta nilai ngan sakali. Asupkeun kana itungan, algoritma basajan ngeunaan hal etaéta saperti di handap ieu:
# Pretend the first number in the list is the largest number.
# Look at the next number, and compare it with this largest number.
# Only if this next number is larger, then keep that as the new largest number.
# RepeatRepéat steps 2 and 3 until you have gone through the whole list.
 
And here is a more formal coding of the algorithm in a [[pseudocode]] that is similar to most [[programming language]]s:
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>5th element of the list.
* ''<='' as used here indicates 'less than or equal to'
 
Note also the algorithm assumes that the list contains at leastléast one number. It will fail when presented an empty list.
Most algorithms have similar assumptions on their inputs, called [[precondition|pre-conditions]].
 
As it happens, most peoplepéople who implement algorithms want to know how much of a particular resource (such as time or storage) a given algorithm requires. Methods have been developed for the [[analysis of algorithms]] to obtain such quantitative answers; for example, the algorithm above has a time requirement of O(''n''), using the [[big O notation]] with ''n'' representing for the length of the list.
 
== Sajarah ==
[[Gambar:1983_CPA_5426.jpg|thumb|A tribute to the originator and namesake of algorithms]]
 
Kecap ''algoritma'' comes ultimately from the name of the [[9th century|9<sup>th</sup>9th-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 earlyéarly [[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.
 
== Kelas algoritma ==
Aya sababaraha cara keur nyieun kelas algoritma, and the merits of eachéach classification have been the subject of ongoing debate.
 
One way of classifying algorithms is by their design methodology or paradigm. There is a certain number of paradigms, eachéach different from the other. Furthermore, eachéach of these categories will include many different types of algorithm. Some commonly found paradigms include:
* Divide and conquer. A [[divide-and-conquer algorithm]] reduces an instance of a problem to one or more smaller instances of the same problem (usually [[recursion|recursively]]), until the instances are small enough to be directly expressible in the [[programming language]] employed (what is 'direct' is often discretionary).
* Dynamic programming. When a problem shows optimal substructure, i.e when the optimal solution to a problem consists of optimal solutions to subproblems (for instance the shortest path between two vertices on a weighted [[Graph (mathematics)|graph]] consists of the shortest path between all the vertices in between.) You solve such a problem bottom-up by solving the simplest problems first and then procceding to increasinglyincréasingly difficult problems until you have solved the original problem. This is called a [[Dynamic programming|dynamic programming algorithm]].
* The greedy method. A [[greedy algorithm]] is similar to a [[Dynamic programming|dynamic programming algorithm]], but the difference is that at eachéach stage you don't have to have the solutions to the subproblems, you can makemaké a "greedy" choice of what looks best for the moment.
* LinearLinéar programming. When you solve a problem using [[linear programming]] you put the program into a number of [[Linear algebra|linear]] [[Inequality|inequalities]] and then try to maximize (or minimize) the inputs. Many problems (such as the [[maximum flow]] for directed [[Graph (mathematics)|graphs]]) can be stated in a linearlinéar programming way, and then be solved by a 'generic' algorithm such as the [[Simplex algorithm]].
* SearchSéarch and enumeration. Many problems (such as playing [[chess]]) can be modelled as problems on [[graph theory|graphs]]. A [[graph exploration algorithm]] specifies rules for moving around a graph and is useful for such problems. This category also includes the [[search algorithm]]s and [[backtracking]].
* The probabilistic and heuristic paradigm. Algorithms belonging to this class fit the definition of an algorithm more loosely. [[Probabilistic algorithm]]s are those that makemaké 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 annealingannéaling' alludes to the metallurgic term meaningméaning the heatinghéating 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 ideaidéa being that the random element will be decreaseddecréased 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 repeatedlyrepéatedly 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.