202 IKSICN AND ANALYSIS of objects

202 IKSICN AND ANALYSIS
of objects or systems under varying conditions. The model itself is usually a representation of objects, events, processes, or systems and is used for prediction and control. Models may be descriptive or explanatory. Manipulation of the model is used to test the im-pact of changes in one or more components of the model on the entity as a whole. In this way tests can be carried out without dis-turbing the subject of the model. The various types of models have been classified into three general groups. We shall distinguish three types of model: iconic, analogue, and symbolic. Roughly, we can say that (1) an iconic model pictorially or visually represents certain aspects of a system (as does a photograph or model airplane); (2) an analogue model employs one set of prop-erties to represent some other set of properties which the system being studied possesses (e.g., for certain purposes, the flow of water through pipes may be taken as an analogue of the "flow" of elec-tricity in wires); and (3) a symbolic model is one which employs symbols to designate properties of the system under study (by means of a mathematical equation or set of such equations)." Scale models and wind tunnels represent an iconic model used to simulate actual flight conditions. In operations research, the word model is used to mean a mathematical description of an activity which expresses the relationships among various elements with sufficient accuracy so that it can be used to predict the actual out-come under any expected set of circumstances. Mathematical models are of many types, depending upon the real-life situations they are designed to represent. They have both advantages and disadvantages as analytical tools. The model, rather than the sys-tem it represents, can be manipulated in a variety of ways until a relatively good solution is found. On the basis of such experimen-tation, the actual system can be adjusted with a minimum of dis-ruption. An obvious disadvantage of model building is the diffi-culty in duplicating reality completely. Also the process, while extremely beneficial, can be time-consuming and costly. Model building provides a tool for extending the researcher's judgment in handling large-scale, complex systems. In a sense, the use of a model frees the intuition and permits it to concentrate on those problems to which it is particularly suited. It permits the creative manager to test rigorously the implications of new plans, new schemes,. and new ideas."
"Churchman, Ackoff, and Arnoff, op. cit., p. 158. '"Franklin A. Lindsay, New Techniques for Management Decision Makins, McGraw-Hill Book Company, New York, 1958, p. 6.
brains," com-puters have not been considered "thinking" machines. The term often is used facetiously because "everyone knows that thinking is a human activity." Nevertheless research has progressed on simu-lating "thinking-like behavior" whet e the goal is, ". . . to construct computer programs which exhibit behavior that we call 'intelli-gent behavior' when we observe it in human beings.' The general approach is one of replicating human problem-solving behavior with heuristic programs--sophisticated trial and error. Problem-Solving behavior typically involves identifying alternatives, assessing their possible consequences, and making a choice. Theoretically the number of alternatives is infinite, but for "all practical purposes" only a few are relevant. Given constraints and sets of criteria the computer program can screen the alterna-tives and pick one. However, there is no guarantee of optimality. If the problem is complex and requires a sequence of decisions (as in most modern organizations), heuristic approaches are even more desirable. Both special-purpose and general-purpose pro-grams have been developed in the research on artificial intelli-gence. Computers also may be useful in algorithmic or "cookbook" approaches to problem solving. For well-structured problems the solution may be obtainable with a precise set of computational steps. For more complex problems an algorithmic approach may suffice by considering a large but finite number of steps. However, computer capacity limitations plus time and cost considerations rule out this approach to solving some problems. The development of programming languages, translators, and compilers has facilitated the researcher's use of computer capabilities. The various specialized techniques can be applied more readily if managers and/or scientists can describe problems

Hasil (Bahasa Indonesia) 1:

202 IKSICN DAN ANALISIS of objects or systems under varying conditions. The model itself is usually a representation of objects, events, processes, or systems and is used for prediction and control. Models may be descriptive or explanatory. Manipulation of the model is used to test the im-pact of changes in one or more components of the model on the entity as a whole. In this way tests can be carried out without dis-turbing the subject of the model. The various types of models have been classified into three general groups. We shall distinguish three types of model: iconic, analogue, and symbolic. Roughly, we can say that (1) an iconic model pictorially or visually represents certain aspects of a system (as does a photograph or model airplane); (2) an analogue model employs one set of prop-erties to represent some other set of properties which the system being studied possesses (e.g., for certain purposes, the flow of water through pipes may be taken as an analogue of the "flow" of elec-tricity in wires); and (3) a symbolic model is one which employs symbols to designate properties of the system under study (by means of a mathematical equation or set of such equations)." Scale models and wind tunnels represent an iconic model used to simulate actual flight conditions. In operations research, the word model is used to mean a mathematical description of an activity which expresses the relationships among various elements with sufficient accuracy so that it can be used to predict the actual out-come under any expected set of circumstances. Mathematical models are of many types, depending upon the real-life situations they are designed to represent. They have both advantages and disadvantages as analytical tools. The model, rather than the sys-tem it represents, can be manipulated in a variety of ways until a relatively good solution is found. On the basis of such experimen-tation, the actual system can be adjusted with a minimum of dis-ruption. An obvious disadvantage of model building is the diffi-culty in duplicating reality completely. Also the process, while extremely beneficial, can be time-consuming and costly. Model building provides a tool for extending the researcher's judgment in handling large-scale, complex systems. In a sense, the use of a model frees the intuition and permits it to concentrate on those problems to which it is particularly suited. It permits the creative manager to test rigorously the implications of new plans, new schemes,. and new ideas." "Churchman, Ackoff dan Arnoff, op. cit., ms. 158. '"Franklin A. Lindsay, teknik-teknik baru untuk manajemen keputusan Makins, McGraw-Hill buku perusahaan, New York, 1958, ms. 6. brains," com-puters have not been considered "thinking" machines. The term often is used facetiously because "everyone knows that thinking is a human activity." Nevertheless research has progressed on simu-lating "thinking-like behavior" whet e the goal is, ". . . to construct computer programs which exhibit behavior that we call 'intelli-gent behavior' when we observe it in human beings.' The general approach is one of replicating human problem-solving behavior with heuristic programs--sophisticated trial and error. Problem-Solving behavior typically involves identifying alternatives, assessing their possible consequences, and making a choice. Theoretically the number of alternatives is infinite, but for "all practical purposes" only a few are relevant. Given constraints and sets of criteria the computer program can screen the alterna-tives and pick one. However, there is no guarantee of optimality. If the problem is complex and requires a sequence of decisions (as in most modern organizations), heuristic approaches are even more desirable. Both special-purpose and general-purpose pro-grams have been developed in the research on artificial intelli-gence. Computers also may be useful in algorithmic or "cookbook" approaches to problem solving. For well-structured problems the solution may be obtainable with a precise set of computational steps. For more complex problems an algorithmic approach may suffice by considering a large but finite number of steps. However, computer capacity limitations plus time and cost considerations rule out this approach to solving some problems. The development of programming languages, translators, and compilers has facilitated the researcher's use of computer capabilities. The various specialized techniques can be applied more readily if managers and/or scientists can describe problems

Hasil (Bahasa Indonesia) 2:

202 IKSICN DAN ANALISIS
objek atau sistem dalam berbagai kondisi. Model itu sendiri biasanya representasi dari objek, peristiwa, proses, atau sistem dan digunakan untuk prediksi dan kontrol. Model mungkin deskriptif atau jelas. Manipulasi model yang digunakan untuk menguji im-pakta perubahan dalam satu atau lebih komponen dari model pada entitas secara keseluruhan. Dengan cara ini tes dapat dilakukan tanpa dis-turbing subjek model. Berbagai jenis model telah diklasifikasikan ke dalam tiga kelompok umum. Kita akan membedakan tiga jenis model: ikonik, analog, dan simbolis. Secara kasar, kita dapat mengatakan bahwa (1) model ikonik pictorially atau visual merupakan aspek-aspek tertentu dari sistem (seperti halnya foto atau model pesawat); (2) model analog mempekerjakan satu set prop-erti untuk mewakili beberapa set lain sifat yang sistem yang sedang dipelajari memiliki (misalnya, untuk tujuan tertentu, aliran air melalui pipa dapat diambil sebagai analog dari "aliran" elec-tricity di kawat); dan (3) model simbolik adalah salah satu yang mempekerjakan simbol untuk menunjuk sifat sistem yang diteliti (dengan cara persamaan matematika atau set persamaan tersebut). "model Skala dan terowongan angin merupakan model ikon yang digunakan untuk mensimulasikan kondisi penerbangan yang sebenarnya . Dalam riset operasi, model kata yang digunakan untuk berarti deskripsi matematis dari suatu kegiatan yang menyatakan hubungan di antara berbagai elemen dengan akurasi yang memadai sehingga dapat digunakan untuk memprediksi model yang sebenarnya out-datang di bawah setiap set yang diharapkan dari keadaan. Matematika yang dari berbagai jenis, tergantung pada situasi kehidupan nyata yang mereka dirancang untuk mewakili. Mereka memiliki kelebihan dan kekurangan sebagai alat analisis. Model, daripada sys-tem yang diwakilinya, dapat dimanipulasi dalam berbagai cara sampai relatif solusi yang baik ditemukan. Atas dasar tersebut experimen-tasi, sistem yang sebenarnya dapat disesuaikan dengan minimal dis-ruption. Sebuah kelemahan yang jelas dari pembentukan model adalah diffi-culty dalam duplikasi realitas sepenuhnya. Juga proses, sementara sangat bermanfaat, bisa memakan waktu dan mahal. Bangunan Model menyediakan alat untuk memperluas penilaian peneliti dalam menangani skala besar, sistem yang kompleks. Dalam arti, penggunaan model membebaskan intuisi dan memungkinkan untuk berkonsentrasi pada masalah-masalah yang itu sangat cocok. Ini memungkinkan manajer kreatif untuk menguji ketat implikasi dari rencana baru, skema baru ,. dan ide-ide baru. "
"rohaniawan, Ackoff, dan Arnoff, op. cit., p. 158. '"Franklin A. Lindsay, Teknik Baru untuk Manajemen Keputusan Makins, McGraw-Hill Book Company, New York, 1958, hal. 6.
otak, "com-puters belum dianggap" berpikir "mesin. Istilah yang sering digunakan berkelakar karena "semua orang tahu bahwa berpikir adalah aktivitas manusia." Namun penelitian telah berkembang pada "perilaku berpikir seperti" Handphone-lating mengasah e tujuannya adalah, "... Membangun program komputer yang menunjukkan perilaku yang kita sebut 'perilaku intelli-gent' ketika kita amati dalam manusia. ' Pendekatan yang umum adalah salah satu mereplikasi perilaku pemecahan masalah manusia dengan program heuristik -.. Trial and error canggih Pemecahan Masalah perilaku biasanya melibatkan identifikasi alternatif, menilai konsekuensinya mungkin, dan membuat pilihan teoritis jumlah alternatif tidak terbatas, tetapi untuk "semua tujuan praktis" hanya sedikit yang relevan. kendala Mengingat dan set kriteria program komputer dapat menyaring alterna-inisiatif-inisiatif dan memilih satu. Namun, tidak ada jaminan dari optimalitas. Jika masalahnya rumit dan membutuhkan urutan keputusan (seperti dalam kebanyakan organisasi modern), pendekatan heuristik bahkan lebih diinginkan. Kedua tujuan khusus dan tujuan umum pro-gram telah dikembangkan dalam penelitian buatan intelli-gence. Komputer juga dapat berguna dalam algoritmik atau "buku resep" pendekatan untuk pemecahan masalah. Untuk masalah yang terstruktur dengan baik solusi mungkin diperoleh dengan set yang tepat dari langkah-langkah komputasi. Untuk masalah yang lebih kompleks pendekatan algoritmik mungkin cukup dengan mempertimbangkan sejumlah besar tapi terbatas langkah. Namun, keterbatasan kapasitas komputer ditambah waktu dan pertimbangan biaya mengesampingkan pendekatan ini untuk memecahkan beberapa masalah. Perkembangan bahasa pemrograman, penerjemah, dan compiler telah memfasilitasi penggunaan peneliti dari kemampuan komputer. Berbagai teknik khusus dapat diterapkan lebih mudah jika manajer dan / atau ilmuwan dapat menjelaskan masalah