The term of artificial intelligence (AI) has some definitions, i.e.:
- A study that is trying to get the thing to be intelligent
- A study to utilize the computer to be able to solve the problem
- The technology that adopts a human intelligence and simulates to solve the problem
The intelligent according to John McCarthy Stanford is an ability to achieve success in the problem solution. So the AI is offering approaches from the media or testing of intelligent theory. Those theories can be expressed in the computer program language and real proven.
The standard computer program only solves programmed problems specifically. If a standard program requires to be changed in the self-adaptation with new information, all programs shall be seen one by one until we get an optimal state to attach a change or modification. This way not only wastes time, but it can also affect certain parts of the program causing errors.
In contrast, Artificial Intelligence can allow computers to ‘think’. By simplifying the program, Artificial Intelligence can mimic the human learning process so that new information can be absorbed and used as a reference in the future. Humans can absorb new information without the need to alter or influence other information that has been stored. Using an Artificial Intelligence program requires a much simpler way than using a standard program without Artificial Intelligence in it.
The techniques used in Artificial Intelligence allow for the creation of a program that each part contains independent and well-identified measures to solve a problem. Each piece of program is like a piece of information in the human mind. If the information is ignored, our minds can automatically adjust how it works to adopt to the new fact or information. We don’t need to always remember every piece of information we have learned. Only relevant to the problems we face that we use. Similarly in Artificial Intelligence, any piece of Artificial Intelligence program can be modified without affecting the structure of the entire program. This flexibility can result in an increasingly efficient and understandable program.
Artificial Intelligence belongs to a relatively young field of science. In the 1950s scientists and researchers began to think of how the machine could do its work as human beings could. Alan Turing, a British mathematician, first proposed a test to see whether or not a machine was said to be intelligent. The test results are then known as the Turing Test, where the machine is disguised as if someone in a game capable of responding to a series of questions asked. Turing assumes that, if the machine can make a person believe that he or she is capable of communicating with others, then it can be said that the machine is intelligent (like a human being).
Artificial Intelligence itself was raised by a professor from the Massachusetts Institute of Technology named John McCarthy in 1956 at the Dartmouth Conference attended by AI researchers. At the conference also defined the main purpose of Artificial Intelligence, namely: knowing and modeling the processes of human thinking and designing the machine to meetings mimic human behavior.
Some of the AI programs that began to be created in 1956-1966, among others:
- Logic Theorist, introduced to the Dartmouth Conference, this program can prove theorems
- Sad Sam, programmed by Robert K. Lindsay (1960). This program can find out simple sentences written in English and able to provide answers to the facts
- ELIZA, programmed by Joseph Weinzenbaum (1967). This program is able to do therapy to patients
The problems that are first handled by Artificial Intelligence are proof of theorems and games. An Artificial Intelligence researcher named Samuel wrote a chess game program that not only played chess, but the program was also created in order to use his experience to improve his abilities. Meanwhile, Newell, a logical theorist trying to prove mathematical theorems.
The rapid development of technology causes the development and expansion of the scope that requires the presence of Artificial Intelligence. Intelligent characteristics have begun to be needed in various disciplines and technologies. Artificial Intelligence isn’t only penetrated in various other disciplines. The wedge between psychology and artificial intelligence gave birth to an area known as cognition & psycholinguistics. The wedge between electro engineering and artificial intelligence gave birth to various sciences such as image processing, control theory, pattern recognition, and robotics.
Today, Artificial Intelligence also contributes considerably to management. The existence of decision support systems and Management Information Systems also can not be separated from the Artificial Intelligence share.
The use of Artificial Intelligence in various disciplines makes it complicated enough to classify Artificial Intelligence according to the disciplines that use it. To facilitate this, the classification of the scope of Artificial Intelligence is based on the given output of the commercial application (although actually Artificial Intelligence itself is not a commercial field).
The main scopes in Artificial Intelligence are:
- Expert System. Here the computer is used as a means to store the knowledge of the experts. Thus the computer will have the expertise to solve the problem by imitating the expertise possessed by
- Natural Language Processing. With natural language processing, it is expected that the user can communicate with a computer using everyday language.
- Speech Recognition. Through the introduction of speech expected human beings can communicate with a computer
- Robotics & Sensory Systems.
- Computer Vision, trying to be able to interpret images or objects visible
- Intelligent Computer-aided Instruction. Computers can be used as tutors who can train
- Game
Along with the development of technology, emerging some technology that also aims to make the computer become intelligent so that it can mimic the work of human every day.
This technology is also able to accommodate the uncertainty and inaccuracy of input data. Based on set theory, then in 1965 came Fuzzy Logic. Then in 1975, John Holland said that any problem in the form of adaptation (natural and artificial) can generally be formulated in genetic terminology. The Genetic Algorithm is a simulation of Darwin’s evolutionary process and genetic operations on chromosomes.
In line with the development of human problems, people must use resources efficiently. To do that, then we need help with the high quality of computers. In human life, computers can help in the areas of:
- Agriculture, computers can control robots that control pests, pruning trees, harvesting.
- Factory, the computer can control the robot who must do the work dangerous and boring, inspection and maintenance
- Health, computers can help to diagnose illness, monitor patient’s condition, and provide treatment
- Housework, a computer can provide advice on cooking and shopping, helping to clean floors, mowing, washing clothes, etc.
When compared to natural intelligence, artificial intelligence has commercial advantages, including:
- Artificial intelligence is more permanent.
- Artificial intelligence is more easily duplicated and disseminated.
- Artificial intelligence can be documented.
Artificial intelligence can do the job faster than with natural intelligence.
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Istilah kecerdasan buatan atau artificial intelligent (AI) mempunyai beberapa definisi, diantaranya:
- Suatu studi yang berusaha membuat cara agar perangkat keras berlaku cerdas
- Suatu studi yang memanfaatkan komputer agar mampu menyelesaikan permasalahan yang sukar
- Teknologi yang mengadopsi prilaku kecerdasan manusia dan mensimulasikannya untuk memecahkan permasalahan
Kecerdasan menurut John McCarthy Stanford adalah suatu kemampuan dalam mencapai kesuksesas dalam memecahkan permasalahan.
Dengan demikian, kecerdasa buatan menawarkan pendekatan dari media atau uji teori kecerdasan. Teori-teori ini dapat dinyatakan dalam bahasa program komputer dan dibuktikan secara nyata.
Program komputer standar hanya mampu menyelesaikan persoalan terprogram secara spesifik. Jika sebuah program standar perlu dirubah untuk menyesuaikan diri dengan suatu informasi baru, seluruh program harus dilihat satu persatu sampai kita dapatkan ruang optimal untuk menyisipkan perubahan atau modifikasi tersebut. Cara seperti ini tidak hanya memboroskan waktu, namun juga dapat mempengaruhi bagian tertentu dari program itu sehingga menyebabkan terjadinya error.
Sebaliknya, Kecerdasan Buatan dapat memungkinkan komputer untuk ‘berpikir’. Dengan cara menyederhanakan program, Kecerdasan Buatan dapat menirukan proses belajar manusia sehingga informasi baru dapat diserap dan digunakan sebagai acuan di masa-masa yang akan datang. Manusia dapat menyerap informasi baru tanpa perlu mengubah atau mempengaruhi informasi lain yang telah tersimpan. Menggunakan program Kecerdasan Buatan membutuhkan cara yang jauh lebih sederhana dibandingkan dengan memakai program standar tanpa Kecerdasan Buatan di dalamnya.
Teknik yang digunakan dalam Kecerdasan Buatan memungkinkan dibuatnya sebuah program yang setiap bagiannya mengandung langkah-langkah independen dan dapat diidentifikasi dengan baik untuk dapat memecahkan sebuah atau sejumlah persoalan. Setiap potong bagian program adalah seperti sepotong informasi dalam pikiran manusia. Jika informasi tadi diabaikan, pikiran kita secara otomatis dapat mengatur cara kerjanya untuk menyesuaikan diri dengan fakta atau informasi yang baru tersebut. Kita tidak perlu selalu mengingat setiap potong informasi yang telah kita pelajari. Hanya yang relevan dengan persoalan yang kita hadapi yang kita gunakan. Demikian pula dalam Kecerdasan Buatan, setiap potong bagian program Kecerdasan Buatan dapat dimodifikasi tanpa mempengaruhi struktur seluruh programnya. Keluwesan ini dapat menghasilkan program yang semakin efisien dan mudah dipahami.
Kecerdasan Buatan termasuk bidang ilmu yang relatif muda. Pada tahun 1950-an para ilmuwan dan peneliti mulai memikirkan bagaimana caranya agar mesin dapat melakukan pekerjaannya seperti yang bisa dikerjakan oleh manusia. Alan Turing, seorang matematikawan Inggris pertama kali mengusulkan adanya tes untuk melihat bisa tidaknya sebuah mesi dikatakan cerdas. Hasil tes tersebut kemudian dikenal dengan Turing Test, dimana si mesin tersebut menyamar seolah-olah sebagai seseorang di dalan suatu permainan yang mampu memberikan respon terhadap serangkaian pertanyaan yang diajukan. Turing beranggapan bahwa, jika mesin dapat membuat seseorang percaya bahwa dirinya mampu berkomunikasi dengan orang lain, maka dapat dikatakan bahwa mesin tersebut cerdas (seperti layaknya manusia).
Kecerdasan Buatan sendiri dimunculkan oleh seorang profesor dari Massachusetts Institute of Technology yang bernama John McCarthy pada tahun 1956 pada Dartmouth Conference yang dihadiri oleh para peneliti AI. Pada konferensi tersebut juga didefinisikan tujuan utama dari Kecerdasan Buatan, yaitu: mengetahui dan memodelkan proses-proses berfikir manusia dan mendesain mesin agar rapat menirukan kelakuan manusia tersebut.
Beberapa program AI yang mulai dibuat pada tahun 1956-1966, antara lain:
- Logic Theorist, diperkenalkan pada Dartmouth Conference, program ini dapat membuktikan teorema-teorema
- Sad Sam, diprogram oleh Robert K. Lindsay (1960). Program ini dapat mengetahui kalimat-kalimat sederhana yang ditulis dalam bahasa Inggris dan mampu memberikan jawaban dari fakta-fakta yang didengar
- ELIZA, diprogram oleh Joseph Weinzenbaum (1967). Program ini mampu melakukan terapi terhadap pasien
Persoalan-persoalan yang mula-mula ditangani oleh Kecerdasan Buatan adalah pembuktian teorema dan permainan (game). Seorang periset Kecerdasan Buatan yang bernama Samuel menuliskan program permainan catur yang tidak hanya sekedar bermain catur, namun program tersebut juga dibuat agar dapat menggunakan pengalamannya untuk meningkatkan kemampuannya. Sementara itu, Newell, seorang ahli teori logika berusaha membuktikan teorema-teorema matematika.
Makin pesatnya perkembangan teknologi menyebabkan adanya perkembangan dan perluasan lingkup yang membutuhkan kehadiran Kecerdasan Buatan. Karakteristik cerdas sudah mulai dibutuhkan di berbagai disiplin ilmu dan teknologi. Kecerdasan Buatan tidak hanya merambah di berbagai disiplin ilmu yang lain. Irisan antara psikologi dan kecerdasan buatan melahirkan sebuah area yang dikenal dengan nama cognition & psycolinguistics. Irisan antara teknik elektro dengan kecerdasan buatan melahirkan berbagai ilmu seperti: pengolahan citra, teori kendali, pengenalan pola dan robotika.
Dewasa ini, Kecerdasan Buatan juga memberikan kontribusi yang cukup besar di bidang manajemen. Adanya sistem pendukung keputusan, dan Sistem Informasi Manajemen juga tidak lepas dari andil Kecerdasan Buatan.
Adanya irisan penggunaan Kecerdasan Buatan di berbagai disiplin ilmu tersebut menyebabkan cukup rumitnya untuk mengklasifikasikan Kecerdasan Buatan menurut disiplin ilmu yang menggunakannya. Untuk memudahkan hal tersebut, maka pengklasifikasian lingkup Kecerdasan Buatan didasarkan pada output yang diberikan yaitu pada aplikasi komersial (meskipun sebenarnya Kecerdasan Buatan itu sendiri bukan merupakan medan komersial).
Lingkup utama dalam Kecerdasan Buatan adalah:
- Sistem Pakar (Expert System). Disini komputer digunakan sebagai sarana untuk menyimpan pengetahuan para pakar. Dengan demikian komputer akan memiliki keahlian untuk menyelesaikan permasalahan dengan meniru keahlian yang dimiliki
- Pengolahan Bahasa Alami (Natural Language Processing). Dengan pengolahan bahasa alami ini diharapkan user dapat berkomunikasi dengan komputer dengan menggunakan bahasa sehari-hari.
- Pengenalan Ucapan (Speech Recognition). Melalui pengenalan ucapan diharapkan manusia dapat berkomunikasi dengan komputer
- Robotika & Sistem Sensor (Robotics & Sensory Systems).
- Computer Vision, mencoba untuk dapat menginterpretasikan gambar atau obyek- obyek tampak
- Intelligent Computer-aided Instruction. Komputer dapat digunakan sebagai tutor yang dapat melatih
- Game
Seiring dengan perkembangan teknologi, muncul beberapa teknologi yang juga bertujuan untuk membuat agar komputer menjadi cerdas sehingga dapat menirukan kerja manusia sehari-hari.
Teknologi ini juga mampu mengakomodasi adanya ketidakpastian dan ketidaktepatan data input. Dengan didasari pada teori himpunan, maka pada tahun 1965 muncul Logika Fuzzy. Kemudian pada tahun1975 John Holland mengatakan bahwa setiap problem berbentuk adaptasi (alami maupu buatan) secara umum dapat diformulasikan dalam terminologi genetika. Algoritma Genetika ini merupakan simulasi proses evolusi Darwin dan operasi genetika atas kromosom.
Sejalan dengan berkembangnya permasalahan manusia, maka manusia harus menggunakan sumber daya secara eficien. Untuk melakukan hal tersebut, maka kita membutuhkan bantuan dengan kualitas yang tinggi dari komputer. Dalam kehidupan manusia, komputer dapat membantu dalam bidang:
- Pertanian, komputer dapat mengkontrol robot yang melakukan kontrol terhadap hama, pemangkasan pohon, pemilihan hasil panen.
- Pabrik, komputer dapat menkontrol robot yang harus mengerjakan pekerjaan berbahaya dan membosankan, inspeksi dan melakukan perawatan
- Kesehatan, komputer dapat membantu untuk mendiagnosis penyakit, melakukan monitoring kondisi pasien, memberikan perawatan
- Pekerjaan Rumah Tangga, komputer dapat memberikan nasihat dalam memasak dan berbelanja, membantu membersihkan lantai, memotong rumput, mencuci pakaian, dan lain-lain
Jika dibanding kecerdasan alami, kecerdasan buatan memiliki keuntungan komersial, antara lain:
- Kecerdasan buatan lebih bersifat permanen.
- Kecerdasan buatan lebih mudah diduplikasi dan disebarkan.
- Kecerdasan buatan dapat didokumentasi.
Kecerdasan buatan dapat mengerjakan pekerjaan lebih cepat dibanding dengan kecerdasan alami.
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