| Bahan Kajian | - Pendahuluan: penjelasan materi kuliah, tata cara, ujian dan daftar pustaka
- Prinsip Dasar Sistem: pengertian sistem, teknik sistem analisa, sistem rujukan, metode delphi
- Metode dan Simulasi: dasar-dasar model, dimensi model, model matematis, model deterministrik, model probabilistik, odel dinamik, simulasi versus solusi analitik validitas model.
- Optimasi: decision variables, fungsi sasaran, persamaan & pertidaksamaan kendala, solusi matematis model linier dan non-linier.
- Analisa Keputusan: pengambilan keputusan pada kondisi pasti, dengan resiko, dan kondisi tidak pasti (uncertainty); kriteria maksimum, minimax, teori probabilitas, strategis Bayes, pohon keputusan.
- Sistem Dinamik: dinamik upan balik (feedback), sistem struktur, batas tertutup, loop umpan balik, persamaan simbol, level, dan laju (rate), mata rantai informasi, diagram alir Dynamo Compiler.
- Program Dinamik: karakteristik program, formulasi model, persamaan / pertidaksamaan batasan, solusi model, dinamika forward dan backward; solusi dari model.
- Analisa Jaringan: karekteristik, formulasi model, analisa jaringan (network), algoritma, jalur kritis, alokasi sumber.
- Analisa Kelayakan: kelayakan teknis, ekonomi, finansial, hukum sosial politik, analisa kepekaan.
- Weighted Ranking Technique: parameter model (factor) penentu, koefisien pemilihan alternatif, matriks pengambilan keputusan.
- Sistem Dinamik: dinamik upan balik (feedback), sistem struktur, batas tertutup, loop umpan balik, persamaan simbol, level, dan laju (rate), mata rantai informasi, diagram alir Dynamo Compiler.
- Model Antrian: karakteristik, proses kedatangan, proses pelayanan disiplin antrian, distribusi poison, distribusi eksponensial, formulasi model, solusi dari model.
- Rantai Markov: aljabar linier, teori probabilitas, matriks transisi probabilitas, matriks fundamental reguler dan absorbing Markov.
- Teori Permainan: Strategi Minimax – Miximin, Teori Laplace, Mixed Strategies dan Expected Payoff Dominan, Algoritma Brown.
| - Introduction: explanation of lecture material, procedures, exams and bibliography
- Basic Principles of Systems: understanding systems, systems analysis techniques, reference systems, Delphi method
- Methods and Simulation: model basics, model dimensions, mathematical models, deterministic models, probabilistic models, dynamic models, simulation versus analytical solutions model validity.
- Optimization: decision variables, target functions, equations & inequalities constraints, mathematical solutions of linear and non-linear models.
- Decision Analysis: decision making under certain conditions, with risk, and uncertain conditions (uncertainty); maximum criterion, minimax, probability theory, strategic Bayes, decision trees.
- Dynamic Systems: feedback dynamics, structural systems, closed boundaries, feedback loops, symbol equations, levels and rates, information chains, Dynamo Compiler flow diagrams.
- Dynamic Programs: program characteristics, model formulation, boundary equations/inequalities, model solutions, forward and backward dynamics; solution of the model.
- Network Analysis: characteristics, model formulation, network analysis, algorithms, critical path, resource allocation.
- Feasibility Analysis: technical, economic, financial, socio-political legal feasibility, sensitivity analysis.
- Weighted Ranking Technique: determining model parameters (factors), alternative selection coefficients, decision making matrix.
- Dynamic Systems: feedback dynamics, structural systems, closed boundaries, feedback loops, symbol equations, levels and rates, information chains, Dynamo Compiler flow diagrams.
- Queue Model: characteristics, arrival process, queuing discipline service process, poison distribution, exponential distribution, model formulation, model solution.
- Markov chains: linear algebra, probability theory, probability transition matrices, regular fundamental matrices and absorbing Markov.
- Game Theory: Minimax – Miximin Strategy, Laplace Theory, Mixed Strategies and Dominant Expected Payoff, Brown's Algorithm.
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