Silabus-S2-MATEMATIKA 2009-2014

[FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM]
[FACULTY OF MATHEMATICS AND NATURAL SCIENCES]
Program Studi
Department
Jenjang Pendidikan
Programme
[JURUSAN MATEMATIKA]
Kompetensi
Lulusan
x
x
AKADEMISI DI BIDANG MATEMATIKA DAN TERAPANNYA
PENELITI DI BIDANG MATEMATIKA DAN TERAPANNYA
Graduate
Competence
x
x
ACADEMICIAN IN MATHEMATICS AND ITS APPLICATIONS
RESEARCHER IN MATHEMATICS AND ITS APPLICATIONS
[MATHEMATICS DEPARTMENT]
PROGRAM PASCA SARJANA (MAGISTER)
STRUKTUR KURIKULUM/COURSE STRUCTURE
No.
Kode MK
Code
SEMESTER I
1
SM092301
2
SM092303
3
SM092305
4
SM092307
SEMESTER II
1
SM092302
2
SM092304
3
4
SM092202
5
SM092204
6
SM092206
7
SM092208
8
SM092210
Nama Mata Kuliah (MK)
Course Title
Aljabar
Algebra
Analisis Fungsional
Functional Analysis
Pemodelan Matematika dan Simulasi
Mathematical Modeling and Simulation
Bioinformatika
Bioinformatics
Jumlah sks/Total of credits
Komputasi Numerik
Numerical Computation
Komputasi Jaringan Syaraf Tiruan
Artificial Neural Network Computation
Mata Kuliah Pilihan
Optimasi Dinamis
Dynamics Optimazation
Logistik dan Metode Perencanaan Transportasi
Logistics and Transportation Planning Method
Teori dan Aplikasi Graf
Theory and Application of Graph
Dispersi Atmosfir
Atmospheric Dispersion
Kecerdasan Buatan
Artificial Intelegence
sks
Credits
3
3
3
3
12
Kurikulum/Curriculum ITS : 2009-2014
POSTGRADUATE PROGRAM (MAGISTER)
3
3
3
3
3
3
3
1
2
SM092203
3
SM092205
4
SM092207
5
SM092209
6
SM092211
7
SM092213
8
SM092215
9
SM092217
10
SM092219
11
SM092221
12
SM092223
13
SM092225
14
SM092227
15
SM092229
16
SM092231
17
SM092233
18
SM092235
19
SM092237
20
SM092239
Aljabar MaxPlus
MaxPlus Algebra
Komputasi Dinamika Fluida
Computational Fluid Dynamics
Kontrol Optimum
Optimum Control
Kapita Selekta Pemodelan dan Simulasi
Special Topic of Modeling and Simulation
Analisis Wavelet
Wavelet Analysis
Kapita Selekta Analisis Terapan
Special Topic of Applied Analysis
Multikriteria Optimum
Optimum Multicriterion
Analisis Time Series
Time Series Analysis
Teori Resiko dan Analisis Keputusan
Risk Theory and Decision Analysis
Sistem Fuzzy
Fuzzy System
Pengolahan Citra
Image Processing
Analisis Data Survival
Data Survival Analysis
Optimasi Heuristik
Heuristic Optimazation
Optimasi Kombinatorial
Combinatorial Optimazation
Kapita Selekta Riset Operasi
Special Topic of Operation Research
Grid Computing
Grid Computing
Data Mining dan Pengenalan Pola
Data Mining and Pattern Recognition
Kapita Selekta Ilmu Komputer
Special Topic of Computer Science
Invers Problem
Invers Problem
Riset Operasi Lanjut
Advanced Operation Research
Jumlah sks/Total of credits
SEMESTER IV
1
SM092306
Tesis
Thesis
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
Kurikulum/Curriculum ITS : 2009-2014
SEMESTER III
1
SM092201
3
3
3
3
3
12
6
Jumlah sks/Total of credits
42
2
DEPARTMENT OF MATHEMATICS
PROGRAM PASCASARJANA/MAGISTER PROGRAM
SILABUS KURIKULUM/COURSE SYLLABUS
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
x
Mahasiswa mampu memahami secara umum struktur
aljabar dan notasinya.
x
The Students will be Understand to the generalize of the
structures algebra and related notion.
x
KOMPETENSI/
COMPETENCY
POKOK
BAHASAN/
SUBJECTS
PUSTAKA
UTAMA/
REFERENCES
Mahasiswa mampu menerapkan aljabar dalam matematika
dan masalah riil
x The students be able to apply algebra in the mathematics
and real problems
x Mahasiswa mampu menganalisis struktur aljabar
x The students able to analyze the structure algebra.
x Mahasiswa mampu menyusun contoh-contoh aplikasi
x The studentds able to contruct some application exsamples
x Grup dan semigrup
x Grup and Semigrup
x Field berhingga dan Polinomial
x Finite field and Polynomial
Spindler K., Abstract Algebra With Applications, Volume I
Macmilan Marcel Dekker.Inc, 1994
Spindler K., Abstract Algebra With Applications, Volume II
Macmilan Marcel Dekker.Inc, 1994.
Lidl R, and G. Pliz, Applied Abstract Algebra: Second Edition,
Spinger Verlag, 1998.
x Subiono, Aljabar, buku ajar Matematika FMIPA ITS, 2009
Kurikulum/Curriculum ITS : 2009-2014
MATA KULIAH/
COURSE TITLE
SM 092301: ALJABAR
(MATA KULIAH WAJIB)
SM 092301: ALGEBRA
(COMPULSARY COURSE TITLE)
Credits: 3 SKS / 3 Credit units
Semester: I
3
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
KOMPETENSI/
COMPETENCY
Mahasiswa
mampu menggunakan analisa secara matematis,
menelaah suatu teorema serta menerapkannya pada masalah
dalam bidang matematika dan bidang lainnya.
The students can do mathematical analysis, study and describe the
thoerems and also aplly those thoerems in mathematical field and
others
x Mahasiswa dapat menjelaskan sifat-sifat ruang vektor, ruang
metrik, ruang normsifat-sifat himpunan, dan sifat-sifat barisan
pada ruang-ruang tersebut
x Mahasiswa dapat menjelaskan sifat-sifat ruang hasil kali dalam,
ortogonalitas vektor dan barisan ortonormal beserta
penggunaanya
x Mahasiswa dapat menerapkan titik tetap Banach untuk
menyelesaikan masalah persamaan linear, persamaan diferensial
dan persamaan integral dan teorema approksimasi pada ruang
norm
Mahasiswa mengerti dan mampu menggunakan teorema spektral
dan kaitannya dengan nilai eigen.
Kurikulum/Curriculum ITS : 2009-2014
MATA KULIAH/
COURSE TITLE
SM 092303 ANALISIS FUNGSIONAL
SM 092303 FUNCTIONAL ANALYSIS
Credits: 3 sks / credits unit
Semester: 1
The students can explain the properties of vector space, metric
space, norm space, set and the properties of sequences in those
spaces.
The studens can explain the properties of inner product,
orthogonality of vector, ortonomality of sequences.
The students can apply the Banach fixed point to linear equation,
differetial equation and integral equation and approximation
theorem in norm space
The students can explain and apply the spectral theorem and its
correlation with eigen vector.
POKOK BAHASAN/
x
Ruang vector, ruang metrics, himpunan buka dan tutup,
4
x
x
x
x
x
x
x
x
x
x
x
x
x
PUSTAKA UTAMA/
REFERENCES
MATA KULIAH/
x
x
konvergensi barisan, barisan Cauchy
Ruang norm, ruang Banach, ruang norm dimensi hingga,
operator linear, operator terbatas
Ruang hasil kali dalam, ruang Hilbert, ortogonal dan komplemen
ortogonal, himpunan dan barisan ortonormal
Teorema Hahn-Banach, dan terapannya pada operator linear
terbatas
Teorema titik tetap Banach dan terapannya pada persamaan
linear, persamaan diferensial, persamaan integral
Teori Approksimasi pada ruang norm, ketunggalan aproksimasi,
aproksimasi seragam
Teori spektral dari operatro linear pada ruang norm untuk
dimensi hingga dan operator linear terbatas.
Vector space, metric space, open and closed set, convergence of
sequences, Cauchy sequence
Norm space, Banach space, finite dimensional of norm space,
linear operator, bounded operator
Inner product space, Hilbert space, ortogonal and complement
ortogonal, ortonormal set and sequences
Hanh-Banach theorem and its application in bounded linear
operator
Banach Fixed point theorem and its application to linear
differential and integral equation
Approximation theory in norm space, uniqueness, uniform
approximation
Spectral theory of linear operator in norm space, in finite
dimension and bounded operator
KREYSZIG, E., INTRODUCTION FUNCTIONAL ANALYSIS WITH
APPLICATION, 1978, JOHN WILEY & SONS
ZEIDLER, E., APPLIED FUNCTIONAL ANALYSIS, 1995, SPRINGER
VERLAG
Kurikulum/Curriculum ITS : 2009-2014
SUBJECTS
SM 092305: PEMODELAN MATEMATIKA DAN
5
COURSE TITLE
SIMULASI
(MATA KULIAH WAJIB)
SM 092305: MATHEMATICAL MODELING AND
SIMULATION
(COMPULSARY COURSE TITLE)
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
x
Mata kuliah ini membahas tentang metode atau teknik untuk
mengkonstruksi model matematika dari fenomena yang akan
dikaji menggunakan hukum-hukum yang mengendalikan
fenomena tersebut
x
This course describes either method or technique to
construct mathematical model of a considered
phenomenon using a governed law of the phenomenon.
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
Konsep dasar pemodelan matematika
Basic concept of mathematical modeling
Pendekatan pembentukan model : eksplorasi data dan
konfirmasi data
Structuring model approach: data exploratory dan data
confirmatory
Pemodelan matematika lanjut
Advanced mathematical modeling
Contoh-contoh pemodelan matematika lanjut
Examples of Advanced mathematical modeling
x
x
KOMPETENSI/
COMPETENCY
x
x
x
x
x
x
x
POKOK BAHASAN/
SUBJECTS
x
x
x
x
x
PUSTAKA UTAMA/
REFERENCES
x
x
Kurikulum/Curriculum ITS : 2009-2014
Credits: 3 SKS / 3 Credit units
Semester: I
Bellomo, N. dan Preziosi, L., Modelling Mathematical Methods
and Scientific Computing, Italy: CRC Press, 1995
Beltrami, E., Mathematical for Dynamic Modelling, New York,
USA: Academic Press,1987
6
x
MATA KULIAH/
COURSE TITLE
Law, A.M. dan Kelton, W.D., Simulation Modelling and Analysis,
New York, USA: Mc Graw Hill,1990
Johansson, R., System Modelling and Identification, New York,
USA: Prentice Hall International, 1993.
SM 092307: BIOINFORMATIKA
(MATA KULIAH WAJIB)
SM 092307: BIOINFORMATICS
(COMPULSARY COURSE TITLE)
Credits: 3 SKS / 3 Credit units
Semester: I
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
x
x
x
x
KOMPETENSI/
COMPETENCY
x
x
x
x
POKOK BAHASAN/
SUBJECTS
x
x
x
x
x
x
x
x
x
Mata kuliah ini membahas tentang metode matematika dan
software tools yang digunakan untuk memodelkan,
mensimulasikan dan memprediksi fungsi DNA.
This course discuss about mathematical method and software
tools which used for modeling, simulate, and prediction of DNA
function.
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
Metode Matematika untuk pemodelan DNA
Mathematical methods for DNA modeling.
Metode komputasi lunak untuk pemodelan DNA
Soft computing for DNA modeling
Konsep dasar biologi molekuler dan data bioinformatics
Basic concept of biology molecular and data bioinformatics
Pengenalan tools bioinformatics
Introduction of bioinformatica tools
Komparasi sequence
Kurikulum/Curriculum ITS : 2009-2014
x
7
x
MATA KULIAH/
COURSE TITLE
Sequence comparations
Pemodelan dan analisis
Modeling and analysis
Polanski, A and M. Kimmel, Bioinformatic, Springer Inc, 2007
Shen, SN and JA TuZynski, Theory and Mathematical Methods
for Bioinformatics, Springer Inc, 2008
Christianini N and MW. Hahn, Computational Genomics,
Cambridge University Press, 2006
SM 092302: KOMPUTASI NUMERIK
(MATA KULIAH WAJIB)
SM 092302: NUMERICAL COMPUTATION
(COMPULSARY COURSE TITLE)
Credits: 3 SKS / 3 Credit units
Semester: II
x
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
KOMPETENSI/
COMPETENCY
POKOK BAHASAN/
SUBJECTS
Matakuliah komputasi numerik ini menjelaskan metode
penyelesaian numerik dari persamaan differensial biasa
dan/atau parsial menggunakan metode beda hingga, elemen
hingga dan volume hingga dengan bantuan komputer
x This course describes numerical solution method of both/either
ordinary differential equation(ODE) and/or partial differential
equation(PDE)using the methods of finite difference, finite
element and finite volume with computer
x Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
x Able to follow development of Mathematics, science and
technology
x Mampu mengembangkan Matematika dan Terapannya
x Able to develop Mathematics and its applications
x Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
x Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
x Masalah Nilai awal dari PD Biasa
x Initial Value Problem of ODE
x Masalah Nilai Batas dari PD Parsial
Kurikulum/Curriculum ITS : 2009-2014
PUSTAKA UTAMA/
REFERENCES
x
x
x
x
x
8
Boundary Value Problem of PDE
Metode Beda Hingga untuk PD Biasa dan Parsial
Finite Difference Method for both ODE and PDE
Metode Elemen Hingga
Finite Element Method
Metode Volume Hingga dan Metode Elemen Batas
Finite Volume Method and Boundary Element Method
x
Hunter, P., FEM/BEM, New Zealand: Dept. of Engineering
Sciences, Auckland University, 2007
Mitchell, A.R & Griffith, D.F., The Finite Difference Method in
Partial Diffrential Equations, New York: A Wiley- Interscience
Publication (John Wiley & Sons) , 1980
Griffiths, D.V. dan Smith, I.A., Numerical Methods for Engineers,
London: Blackwell Scientific Publications, 1991
Whye-Teong Ang, A Beginner's Course in Boundary Element
Methods, New York: 2007
x
PUSTAKA UTAMA/
REFERENCES
x
x
MATA KULIAH/
COURSE TITLE
SM 092305: KOMPUTASI JARINGAN
SYARAF TIRUAN
(MATA KULIAH WAJIB)
SM 092305: COMPUTATION OF ARTIFICIAL
NEURAL NETWORKS
(COMPULSARY COURSE TITLE)
Kurikulum/Curriculum ITS : 2009-2014
x
x
x
x
x
x
x
Credits: 3 SKS / 3 Credit units
Semester: II
TUJUAN
PEMBELAJARAN/
LEARNING
x
Matakuliah komputasi jaringan syaraf tiruan menjelaskan
algoritma-algoritma yang dipakai untuk memodelkan data
dengan
bantuan
komputer.
Mahasiswa
mampu
menterjemahkan langsung algoritma menjadi
program
9
KOMPETENSI/
COMPETENCY
POKOK BAHASAN/
SUBJECTS
PUSTAKA UTAMA/
REFERENCES
komputer dan dipakai untuk menyelesaikan masalah-masalah
pengenalan pola, peramalan, klasifikasi, klustering dan optimasi.
x This course describes the algorithms that used to model data
using computer. Student be able to translate the algorithms
become computer program and used to solve the problems of
pattern recognition, forecasting, classification, clustering and
optimization
x Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
x Able to follow development of Mathematics, science and
technology
x Mampu mengembangkan Matematika dan Terapannya
x Able to develop Mathematics and its applications
x Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
x Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
x Pemdelan JST dari JSB
x Modeling ANN from BNN
x Review pemrograman computer
x Review computer programming
x Masalah klasifikasi sederhana menggunakan perceptron, hebb
dan adaline
x Simple classification problems using perceptron, heb, and adaline
x Metode pengenalan pola menggunakan Hebb, Associative
Memory, BAM, dan MLP
x Pattern recognition methods using Hebb, Associative Memory,
BAM, and MLP
x Metode klasifikasi menggunakan MLP, RBF, jaringan recurrent,
dan LVQ,
x Classification methods using MLP, RBF, Recurrent Network and
LVQ
x Metode peramalan menggunakan MLP, RBF, dan Recurrent
Network
x Forecasting methods using MLP, RBF, and Recurrent Network
x Metode clustering menggunakan Kohonen SOM dan SVM
x Clustering methods using Kohonen SOM and SVM
x Metode Optimasi menggunakan Kohonen, dan Hopfield
x Optimization methods using Kohonen and Hopfield
x Fausett,L, Fundamentals of Neural Networks,Prentice Hall, New
Jersey, USA, 1994.
x Hassoum, MH, Fundamental of Artificial Neural Networks, MIT,
1995.
x Bishop, C, Neural Networks for Pattern Recoqnitions, Oxford
Kurikulum/Curriculum ITS : 2009-2014
OBJECTIVES
10
x
MATA KULIAH/
COURSE TITLE
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
SM 092202: OPTIMASI DINAMIS
(MATA KULIAH PILIHAN)
SM 092202: DYNAMICS OPTIMIZATION
(ASSORTED COURSE TITLE)
Credits: 3 sks / credits unit
Semester: II
x Memberikan pemahaman kepada mahasiswa tentang
optimisasi dan aplikasinya
x To provide the student with an understanding of the
optimization and their applications
x
x
KOMPETENSI/
COMPETENCY
x
x
x
x
POKOK BAHASAN/
SUBJECTS
University Press, 1996
Duda, RO, Hart, PE, Stork, DG, Pattern Classification, John Wiley
and Sons, 2001
Stork, DG and E. Yom-Tov, Computer Manual in MATLAB to
Accompany Pattern Classification, Second Edition (Paperback),
John Wiley and Sons, 2004
x
x
x
x
x
x
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
Kurikulum/Curriculum ITS : 2009-2014
x
Pengantar desain
Introduction to Design,
Perumusan Masalah desain opt8imum
Optimum Design Problem Formulation,
Metode optimasi grafis
Graphical Optimization Method,
11
PUSTAKA UTAMA/
REFERENCES
MATA KULIAH/
COURSE TITLE
Konsep desain optimum
Optimum Design Concepts,
Metode Numerik untuk desain optimum tak terkendala
Numerical Methods for Unconstrained Optimum Design,
Metode Numerik untuk desain optimum terkendala
Numerical Methods for Constrained Optimum Design
Arora, J.S. Introduction to Optimum Design, Elsevier Academics
Press, 2004.
Bryson, A.E., Dynamics Optimizatio, Wiley , 2000
SM 092204: LOGISTIK DAN METODE
PERENCANAAN TRANSPORTASI
(MATA KULIAH PILIHAN)
SM 092204: LOGISTIC AND TRANSPORTATION
PLANNING METHODS
(ASSORTED COURSE TITLE)
Credits: 3 SKS / 3 Credit units
Semester: II
x
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
x
x
KOMPETENSI/
COMPETENCY
x
x
x
Kuliah ini mendiskusikan tentang penjadwalan proyek,
penjadwalan job-shop, penjadwalan sistem asemble
fleksibel, penjadwalan lot economis, perencanaan dan
penjadwalan dalam transportasi.
The course discuss about project scheduling, job shop
scheduling, scheduling of flexible assembly systems,
economic lot scheduling, and planning and scheduling in
supply chains. It covers four areas in services, namely,
reservations and timetabling, tournament scheduling,
planning and scheduling in transportation
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Kurikulum/Curriculum ITS : 2009-2014
x
x
x
x
x
x
12
x
POKOK BAHASAN/
SUBJECTS
x
x
x
x
x
x
x
x
x
x
x
x
PUSTAKA UTAMA/
REFERENCES
x
x
MATA KULIAH/
COURSE TITLE
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
Pengantar sistem logistic
Introduction of logistics system
Meramalkan kebutuhan logistic
Forecasting logistics demand
Merencanakan jaringan logistic
Planning logistics networks
Menyelesaikan masalah manajemen persediaan
Solving inventory management problem
Merancang dan mengoperasikan gudang
Design and operating a warehouse
Merancang dan mengatur angkutan transportasi jarak dekat dan
jauh
Design and manage short/long haul transportation
Ghiani, G, Laporte, G and R. Musmanno, An Introduction to
Logistics Systems Planning and Control, John Wiley and Sons,
Ltd, 2004
Pinedo, ML, Planning and Scheduling in Manufacturing
and Services, Springer Science, 2005
SM 092206 TEORI DAN APLIKASI GRAF
(MATA KULIAH PILIHAN)
SM 092206 GRAPH THEORY AND APPLICATIONS
(MATA KULIAH PILIHAN)
Kurikulum/Curriculum ITS : 2009-2014
x
Credits: 3 SKS / 3 Credit units
Semester: II
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
Agar memahami graph sebagai salah satu model matematika yang
sangat penting untuk berbagai masalah.
To provide the student with an understanding of the graph theory as
a mathematical model for solving mathematical problem
13
KOMPETENSI/
COMPETENCY
POKOK BAHASAN/
SUBJECTS
Pendahuluan (Pengertian Graph, beberapa jenis graph, graph pohon
(pohon minimum), masalah lintasan terpendek, Graph planar
(pengertian graph planar dan graph bidang), graph Euler (pengertian
graph Euler dan semi Euler), graph Hamilton, pewarnaan graph
(pewarnaan titik, pewarnaan sisi), masalah perjodohan, graph
bipartite, graph berarah (turnamen, alur lalu lintas, network).
x
x
PUSTAKA UTAMA/
REFERENCES
x
MATA KULIAH/
COURSE TITLE
F. Hanary, ”Graph Theory”, Addison-Wesley Publishing Co
Inc., Massachussets USA, 1969
Deo Narscyh, “Graph Theory with Applications to
Engineering and computer science Preslitice Hall Inc.,
Englewod Cliffs, N.J., USA
I Ketut Budayasa, “Teori Graph and Aplikasinya”, Unesa
University Press, 2007
SM 092208: DISPERSI ATMOSFIR
(MATA KULIAH PILIHAN)
SM 092208: ATMOSPHERIC DISPERSION
(ASSORTED COURSE TITLE)
Kurikulum/Curriculum ITS : 2009-2014
Introduction, graph tree, shortest distance problem, planar graph,
Euler graph, Hamilton graph, Colouring graph, matching problem,
bipartite graph, directed graph.
Credits: 3 SKS / 3 Credit units
Semester: II
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
KOMPETENSI/
x
x
x
Memberikan wawasan tentang teori dispersi atmosfir dan
menjelaskan tentang prinsip-prinsip dasar tentang
pemodelan dispersi atmosfir
To give an introduction to the theory of atmospheric
dispersion and to describe the basic principles of
atmospheric dispersion modelling
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
14
x
x
x
x
x
POKOK BAHASAN/
SUBJECTS
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
PUSTAKA UTAMA/
REFERENCES
x
x
x
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
Pengangkutan skalar pada Atmosfir
Scalar Transport in the Atmosphere
Proses-proses pengangkutan
Transport Processes
Lapisan batas atmosfir
The Atmospheric Boundary Layer
Sumber-sumber titik penghasil polutan yang kontinyu
Continuous Point Sources of Pollutant
Dispersi pada lingkungan nyata
Dispersion in Real Environments
Kepulan Asap Gauss dari cerobong yang tinggi
Gaussian Plumes from High Chimneys
Deposisi
Deposition
Tipe-tipe dari model dispersi atmosfir
Types of Atmospheric Dispersion Models
Reaksi-reaksi kimiawi dari polutan yang ada di atmosfir
Chemical Reaction of Atmospheric Pollutants
Pembaganan pada Penyelesaian Numerik
Numerical Schemes
Barrat, R., Atmospheric Dispersion Modelling, 1st Edition,
Earthscan Publications, 2001
Colls, J., Air Pollution, 1st Edition, Spon Press (UK), 2002
European Process Safety Centre, Atmospheric Dispersion, 1st
Edition, Rugby: Institution of Chemical Engineers, 1999
Schnelle, K.B. and Dey, P.R., Atmospheric Dispersion Modeling
Compliance Guide, 1st Edition, McGraw-Hill Professional, 1999
Turner, D.B., Workbook of Atmospheric Dispersion Estimates: An
Introduction to Dispersion Modeling, 2nd Edition, CRC Press,
1994
Zannetti, P., Air pollution modeling : theories, computational
methods, and available software, Van Nostrand Reinhold, 1990
Kurikulum/Curriculum ITS : 2009-2014
COMPETENCY
15
MATA KULIAH/
COURSE TITLE
SM 092210: KECERDASAN BUATAN
(MATA KULIAH PILIHAN)
SM 092210: ARTIFICIAL INTELLIGENCE
(ASSORTED COURSE TITLE)
x
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
x
x
x
KOMPETENSI/
COMPETENCY
x
x
x
x
POKOK BAHASAN/
SUBJECTS
x
x
x
x
x
x
x
x
x
x
x
x
Matakuliah kecerdasan buatan mendiskusikan metode merubah
komputer menjadi cerdas yang mampu bernalar sebaik
manusia. Dalam kuliah ini mahasiswa dituntut untuk bisa
mengimplementasikan beberapa metode agar komputer bisa
menjadi cerdas dan bisa menyelesaikan suatu masalah yang
membutuhkan kecerdasan dalam menyelesaikanya.
Artificial Intelligence course discuss the methods to change the
computer become intelligence able to reasoning as well as
human. In this course student should implemented some
methods in order give intelligence to the computer and able to
solve a problem that need intelligence.
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
konsep kecerdasan buatan,
concept of artificial intelligence
teknik penyelesaian masalah menggunakan kecerdasan buatan
problem-solver technique using artificial intelligence
teknik pencarian, representasi pengetahuan, ketidakpastian
searching technique, knowledge representation, uncertainty
sistem pakar, and sistem pakar fuzzy
expert system and fuzzy expert system
algoritma genetika dan pemrograman genetika
genetics algorithms and genetic programming
particle swarm optimization dan algoritma koloni semut
particle swarm optimization and ant koloni algorithms
Kurikulum/Curriculum ITS : 2009-2014
Credits: 3 SKS / 3 Credit units
Semester: III
16
x
x
MATA KULIAH/
COURSE TITLE
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
KOMPETENSI/
COMPETENCY
Stuart J. Russel and Peter Norvig, Artificial Intelligence A
Modern Approach, McGrawHill, 2003
Eleane Rich and Kevin Knight, Artificial Intelligence,
McGrawHill, 2000
John Durkin, Expert Systems: design and development,
Prentice Hall, 2003
SM 092212: MATEMATIKA SISTEM
(MATA KULIAH PILIHAN)
SM 092212: MATEMATICAL SYSTEM
(ASSORTED COURSE TITLE)
Credits: 3 SKS / 3 Credit units
Semester: II
x
Mahasiswa mengerti secara umum matematika sistem dan
notasi yang berhubungan, teori ruang keadaan,
keterkontrolan dan stabilitas
x The Students understand to the generalize of matematical
system and relate notion, the State Space Theory,
controlability and the Stability
x Mahasiswa bisa menggunakan hukum konservasi, prinsipprinsip fenomena dan fisika untuk membuat model
matematika dari sistem
x The
Students
can
use
conservation
laws,
phenomenological and physical principles to make
mathematical models of systems
x Mahasiswa mampu melinierisasi dari sistem nonlinear dan
menyelesaikan sistem differensial linier
x The Students able to linearize of non linear system and
solve linear differential systems.
x Mahasiswa mampu menganalisis keterkontrolan dan
keteramatan dari sistem
x The students able to analyze the controllability and
observability of systems
x Mahasiswa mampu menganalisa perilaku input-output dari
sistem
x The students able to analyze the Input Output Behaviour of
the systems
x Mahasiswa mampu menerapkan keterkontrolan sistem
untuk menstabilkan sistem
x The students able to apply controllability of system to
stabilize the systems
Kurikulum/Curriculum ITS : 2009-2014
x
PUSTAKA UTAMA/
REFERENCES
17
x
POKOK BAHASAN/
SUBJECTS
PUSTAKA UTAMA/
REFERENCES
MATA KULIAH/
COURSE TITLE
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
KOMPETENSI/
COMPETENCY
x
x
x
x
x
x
x
x
x
Mahasiswa mampu menetapkan kriteria kestabilan dari
sistem
The students able to determine the stability criteria of the
systems
Model-model matematika
Mathematical Models
Pengantar teori ruang keadaan
Introduction to State Space Theory
Teori stabilitas
Stability Theory
Subiono, Matematika Sistem, Versi 2.0, buku ajar Jurusan
Matematika FMIPA-ITS, 2010.
Olsder G.j. and J.W. van der Woude, “Mathematical
Systems Theory”, Delft Uitgavers Maatschappij, 1994.
Hinrichsen D. and T. Pritchard “ Mathematical Systems
Theory I Modelling, State Space Analysis, Stability and
Robustness”, Springer Verlag ,2004
SM 092214 ASIMILASI DATA
SM 092214 DATA ASSIMILATION
Credits: 3 sks / credits unit
Semester: 2
Mahasiswa mengerti dan mampu menerapkan berbagai algoritma
dalam asimilasi data pada masalah identifikasi parameter dan
estimasi variable keadaan dari system dinamik stokastik.
Kurikulum/Curriculum ITS : 2009-2014
x
The students understand and can apply the algorithms of data
assimilation to identify parameters and estimate the state variable
of dynamical stochastic system.
x Mahasiswa mengerti metode asimilasi data dan model-model
sistem dimana metode asimilasi data dapat digunakan.
x Mahasiswa mampu menjelaskan beberapa metode estimasi dan
perkembangan metode asimilasi data.
x Mahasiswa dapat menerapkan asimilasi data pada model dinamik
stokastik dan deterministik
x Mahasiswa mampu menjelaskan dan menerapkan berbagai
perkembangan algoritma filter Kalman dalam asimilasi data.
18
x
PUSTAKA UTAMA/
REFERENCES
x
MATA KULIAH/
COURSE TITLE
TUJUAN
PEMBELAJARAN/
LEWIS, J.M., LAKSHMIVARAHAN, DHALL, S.K., 2006, DYNAMIC
DATA ASSIMILATION: A LEAST SQUARES APPROACH,
CAMBRIDE
KALNAY,
2003,
ATMOSPHERIC
MODELING,
DATA
ASSIMILATION AND PREDICTABILITY, CAMBRIDGE
Kurikulum/Curriculum ITS : 2009-2014
POKOK BAHASAN/
SUBJECTS
x The students understand about data assimilation method and
where it’s can be applied.
x The students can explain several estimation methods and the
pathways into data assimilation
x The students can apply data assimilation to dynamical
stochastic/deterministic model
x The students can explain and apply the developing of Kalman filter
as data assimilation method.
x
Pengertian metode asimilasi data: peramalan, model,
keteramatan, analisa sensitivitas, predictable.
x
Model-model yang digunakan dalam asimilasi data
x
Beberapa metode asimilasi data: Model statis stokastik, model
dinamik deterministic, model dinamik stokastik
x
Beberapa perkembangan algoritma Kalman Filter: Extended
Kalman Filter, RRSQRT filter, Ensemble Kalman Filter, Hibrid
filter
x
Studi kasus penerapan asimilasi data
x
Data assimilation: forecasting, modeling, observations,
sensitivity analysis
x
Modeling in data assimilation
x
Some of data assimilation methods: stochastic static model,
deterministic dynamic model, stochastic dynamic model
x
The advantage of Kalman filter: extended Kalman filter,
RRSQRT filter, Ensemble Kalman Filter, Hibrid filter
x
Case studies
SM 092201: ALJABAR MAX PLUS
(MATA KULIAH PILIHAN)
SM 092201: MAX PLUS ALGEBRA
(ASSORTED COURSE TITLE)
Credits: 3 SKS / 3 Credit units
Semester: III
x
Mahasiswa mengerti secara umum aljabar max plus dan
notasinya, teori spektral, perilaku kualitatif periodik dan
asimtotik, dan vektor siklus waktu.
19
x
x
x
KOMPETENSI/
COMPETENCY
x
x
x
x
POKOK BAHASAN/
SUBJECTS
x
x
x
x
x
x
x
x
x
x
x
x
x
PUSTAKA UTAMA/
REFERENCES
x
The Students understand to the generalize of max-plus
algebra and related notion, the spectral theory, periodic
and asymphotic qualitative behavior and the cycle time
vector.
Mahasiswa mampu menerapkan aljabar maxplus di
masalah nyata
The Students be able to apply max-plus algebra in the real
problems
Mahasiswa mampu mampu mendapatkan nilai eigen dan
vektor eigen dari matriks-matriks irreducible dan reducible
The students able to find eigenvalues and eigenvectors of
irreducible an reducible matrices.
Mahasiswa mampu menganalisis perilaku periodik dari
model linier max-plus
The students able to analyze the periodic behavior of the
max plus linear model.
Aljabar Max-Plus
Max-Plus Algebra
Teori Spektral
Spectral Theory
Perilaku periodik dan vektor siklus waktu
Periodic behavior and the cycle-time vector
Perilaku kualitatif asimtotik
Asympotic Qualitative Behavior
Prosedur numerik dari nilai eigen matriks irreducible dan
reducible
Numerical Procedure of eigenvalues of irreducible and
reducible matrices
Introduction to Petri Nets
Subiono, Aljabar Max-Plus, buku ajar Jurusan Matematika
FMIPA-ITS, 2010.
Olsder G.j., Heidegott B. and J.W. van der woude, Maxplus
at Work, Modelling and Analysis of Synchronized System :
A Course on Max-Plus Algebra and ITS Applications,
Princeton University Press, 2006
Subiono, andJ.W. van Wounde, “Power Algorithms for
(mas,+) – and Bipartite(Min,max,+) - Systems”, Discreate
Event Dynamic System : Theory and Applications, Volume
10, pp 369-389, 2002
C.G. Cassandras and Stephane Lafortune, Introduction to
Discrete Event Systems, Second Edition, Springer, 2008
Kurikulum/Curriculum ITS : 2009-2014
LEARNING
OBJECTIVES
20
MATA KULIAH/
COURSE TITLE
SM 092203: KOMPUTASI DINAMIKA FLUIDA
(MATA KULIAH PILIHAN)
SM 092203: COMPUTATIONAL FLUID DYNAMICS
(CFD)
(ASSORTED COURSE TITLE)
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
x
x
Matakuliah komputasi dinamika fluida ini membahas tentang
penggunaan komputer dan teknik numerik untuk
menyelesaikan permasalahan yang berkaitan dengan aliran
fluida
The computational fluid dynamics course describes the
use of computers and numerical techniques to solve
problems involving fluid flow
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
Persamaan aliran fluida
x
Fluid flow equation
x
Persamaan Pengangkutan Skalar
x
Scalar transport equation
x
Persamaan momentum
x
Momentum equation
x
Turbulen
x
Turbulence
x
x
x
KOMPETENSI/
COMPETENCY
x
x
x
x
POKOK BAHASAN/
SUBJECTS
Kurikulum/Curriculum ITS : 2009-2014
Credits: 3 SKS / 3 Credit units
Semester: III
21
Model Turbulen dalam KDF
x
Turbulence modeling on the CFD
x
Proses Komputasi Dinamika Fluida
x
The Computational Fluid Dynamics Process
x
Anderson, J. D. Jr., Computational Fluid Dynamics (The Basics
with Applications), International Edition, New York, USA: Mc
Graw-Hill, 1995
Hoffmann, K. A. and Chiang, S. T., Computational Fluid Dynamics
For Engineers, Wichita, USA: Engineering Education System,
1995
Chung, T.J., Computational Fluid Dynamics, Cambridge:
Cambridge University Press, 2002
Welty, J.R., et al., Fundamentals of Momentum, Heat and Mass
Transfer, 3rd Edition, New York, USA: John Wiley & Sons, Inc.,
1995
Versteeg, H.K. and Malalasekera, W., An Introduction to
Computational Fluid Dynamics – The Finite Volume Method,
Second Edition, England: Prentice Hall - Pearson Education Ltd.,
2007.
Tu, J.Y., Yeoh, G.H. and Liu, G.Q., Computational Fluid DynamicsA Practical Approach, Oxford, UK: Butterworth-Heinemann
Publications, 2008
Yeoh, G.H. and Yuen, K.K., Computational Fluid
Dynamics in Fire Engineering, Oxford, UK: ButterworthHeinemann Publications, 2009
x
x
PUSTAKA UTAMA/
REFERENCES
x
x
x
x
MATA KULIAH/
COURSE TITLE
TUJUAN
Kurikulum/Curriculum ITS : 2009-2014
x
SM 092205: KONTROL OPTIMUM
(MATA KULIAH PILIHAN)
SM 092205: OPTIMAL CONTROL
(ASSORTED COURSE TITLE)
Credits: 3 sks / credits unit
Semester: 3
x
Memberikan kepada mahasiswa pemahaman tentang masalah
22
control optimal, pemodelan, aplikasi, simulasi dan komputasi
x
To provide the student with an understanding of the optimal
control problem, modelling, application, simulation and
computation.
x
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
x
KOMPETENSI/
COMPETENCY
x
x
x
x
x
x
x
x
POKOK BAHASAN/
SUBJECTS
PUSTAKA UTAMA/
REFERENCES
x
x
x
x
x
x
x
x
x
x
1.
2.
x
x
Review kalkulus variasi
Review calculus of variation,
Kontrol optimal: system waktu diskrit dan system waktu
kontinyu
optimal control: Discrete-time systems and continuoustime systems,
Kontrol optimal terkendala dan tak terkendala
unconstrained and constrained optimal control,
waktu akhir tetap dan bebas
fixed and free final time,
Aplikasi dan simulasi
application and simulation,
metode langung dan tak langsung
direct and indirect method,
Komputasi control optimal
computational optimal control.
Subchan, S and Zbikowski, R., Computational Optimal
Control: Tools and Practice, Wiley, 2009.
Lewis, F. dan Syrmos Vassilis, Optimal Control, John
Wiley & Sons, Singapore, 1995.
Kamien, ML and Schwartz, N.L., Dynamic Optimizatio,
North-Holland, Amsterdam, 1993.
Lewis F., Optimal Estimation, John Wiley & Sons,
Singapore, 1986.
Kurikulum/Curriculum ITS : 2009-2014
PEMBELAJARAN/
LEARNING
OBJECTIVES
23
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
x
Menyiapkan mahasiswa pemahaman topic-topik saat ini tentang
pemodelan dan simulasi
x
To provide the student with an understanding of the current
research topic in modelling and simulation
x
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
Tergantung kepada dosen pengampu, akan diinformasikan
kepada mahasiswa sebelum masa perkuliahan
x
KOMPETENSI/
COMPETENCY
x
x
x
x
x
POKOK BAHASAN/
SUBJECTS
Kurikulum/Curriculum ITS : 2009-2014
MATA KULIAH/
COURSE TITLE
SM 092207: KAPSEL PEMODELAN DAN
SIMULASI
(MATA KULIAH PILIHAN)
SM 092207: SELECTED TOPICS OF
MODELING AND SIMULATION
(ASSORTED COURSE TITLE)
Credits: 3 sks / credits unit
Semester: III
Depend on the lecture, it will be informed to the student before
semester begin
PUSTAKA UTAMA/
REFERENCES
24
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
KOMPETENSI/
COMPETENCY
POKOK BAHASAN/
SUBJECTS
Kredit: 3 sks
Credits: 3 credits unit
Semester: I
Diharapkan mahasiswa mendapat pengetahuan dan pemahaman
tentang pokok-pokok analisis fungsional, khususnya tentang ruang
Banach, ruang Hilbert, dan operator linear kompak, serta mengenal
plikasinya.
After completing this course, the students should have knowledge
and comprehension of fundamental concept of functional analysis,
especially about Banach spaces, Hilbert spaces, and compact linear
operators, and be acquainted to their applications.
x Dapat mengenali ruang Banach dan ruang Hilbert, berserta sifatsifat utamanya.
x Dapat menunjukkan sifat-sifat operator linear terbatas, operator
kompak, dan dapat membuktikan sifat-sifat utama operator
kompak.
x Dapat membuktikan kelengkapan ruang Lp, dan mengenal
penerapnnya.
Kurikulum/Curriculum ITS : 2009-2014
MATA KULIAH/
COURSE TITLE
SM 092303 ANALISIS FUNGSIONAL
SM 092303 FUNCTIONAL ANALYSIS
x Able to identify Banach spaces and Hilbert spaces, and address
their main properties.
x Able to show the main properties of bounded linear operators and
compact operators, and prove the fundamental properties of
compact operators.
x Able to prove the completeness of the Lp spaces, and understand
their applications.
x Ruang Banach dan ruang Hilbert: pelengkapan, operator terbatas,
jumlahan langsung, basis ortonormal, jumlahan ortogonal.
x Operator-operator kompak: definisi dan sifat-sifat pokok, teorema
spektral untuk operator simetrik kompak.
x Integrasi Lebesgue: fungsi terukur, integral Lebesgue, pengertian
“hampir dimana-mana”, ruang Lebesgue Lp, kelengkapan ruang Lp.
x Dual dari Lp: dekomposisi ukuran, ukuran kompleks, dual dari Lp
25
x Banach and Hilbert spaces: completion, bounded operators, direct
sum, orthonormal basis, orthogonal sum.
x Compact operators: definition and basic properties, spectral
theorem for compact symmetric operators.
x Lebesgue integration: measurable functions, Lebesgue integral,
the terminology of “almost everywhere”, Lebesgue space Lp,
completeness of Lp.
p
x The dual of L : decomposition of measure, complex measure, the
p
dual of L .
MATA KULIAH/
COURSE TITLE
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
x Zeidler, E., “Applied Functional Analysis, Application to
Mathematical Physics”, Springer-Verlag, New York, 1995.
Conway, J. B., “A Course in Functional Analysis”, Graudate Text
in Mathematics, 96, Springer-Verlag, New York, 1990.
SM 092211: KAPSEL ANALISIS TERAPAN
(MATA KULIAH PILIHAN)
SM 092211: SELECTED TOPICS OF
APPLIED ANALYSIS
(ASSORTED COURSE TITLE)
Credits: 3 sks / credits unit
Semester: III
x
Kurikulum/Curriculum ITS : 2009-2014
PUSTAKA UTAMA/
REFERENCES
Menyiapkan mahasiswa pemahaman topic-topik saat ini
tentang pemodelan dan simulasi
x To provide the student with an understanding of the
current research topic in modelling and simulation
x
KOMPETENSI/
COMPETENCY
x
x
x
x
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
26
x
x
POKOK BAHASAN/
SUBJECTS
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
Tergantung kepada dosen pengampu, akan diinformasikan
kepada mahasiswa sebelum masa perkuliahan
Depend on the lecture, it will be informed to the student before
semester begin
MATA KULIAH/
COURSE TITLE
SM 092213: MULTI-KRITERIA OPTIMUM
(MATA KULIAH PILIHAN)
SM 092307: MULTICRITERIA OPTIMIZATION
(ASSORTED COURSE TITLE)
Credits: 3 SKS / 3 Credit units
Semester: I
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
x
x
x
x
KOMPETENSI/
COMPETENCY
x
x
x
x
POKOK BAHASAN/
SUBJECTS
x
x
x
Mahasiswa mampu membuat model keputusan dalam
menyelesaikan masalah yang berkarakteristik multicriteria
secara optimal
Student able to model decision making to solve problem which
have optimal multicriteria characteristic
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
Klasifikasi masalah multikriteria
Efisiensi dan nondominansi
Metode jumlahan terbobot
Kurikulum/Curriculum ITS : 2009-2014
PUSTAKA UTAMA/
REFERENCES
27
MATA KULIAH/
COURSE TITLE
x
Teknik skalarisasi
Metode non skalarisasi
Multikriteriapemrograman linier
Metode multi objektif simplex
Multiobjektive criteria optimisasi
Matthias Ehrgott, Multicriteria Optimization, Springer
Verlang Berlin, 2005
Statnikov R.B., Multicriteria Design: Optimization and
Identification, Kluwer Academic Publisher, 1999
SM 092215: ANALISIS TIME SERIES
(MATA KULIAH PILIHAN)
SM 092215: TIME SERIES ANALYSIS
(ASSORTED COURSE TITLE)
Credits: 3 SKS / 3 Credit units
Semester: III
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
x
x
x
x
KOMPETENSI/
COMPETENCY
x
x
x
x
POKOK BAHASAN/
SUBJECTS
x
x
x
Kuliah ini mendiskusikan karakteristik dari time-series, dasardasar regresi, teknik untuk data time series, pemodelan
univariate ARIMA, proses GARCH, dan multivariate ARMAX.
The course discusses the characteristics of time series, a
background in regression , techniques for time series data,
univariate ARIMA modeling, GARCH processes, and multivariate
ARMAX models.
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
Karakteristik dari time series
characteristics of time series
Pengantar konsep-konsep dasar dari model plot waktu
Kurikulum/Curriculum ITS : 2009-2014
PUSTAKA UTAMA/
REFERENCES
x
x
x
x
x
x
28
x
x
x
x
PUSTAKA UTAMA/
REFERENCES
x
x
MATA KULIAH/
COURSE TITLE
introducing the fundamental concepts of time plot models
Latar belakang dalam regresi
background in regression
teknik-teknik untuk data time-series
techniques for time series data dan nonstatsioner
pemodelan univariate ARIMA
univariate ARIMA modeling
proses-proses GARCH, model threshold, regresi dengan erroreror autokorelasi, regresi tundaan, pemodelan fungsi alih
GARCH processes, threshold models, regression with
autocorrelated errors, lagged regression, transfer function
modeling
Model-model multivariate ARMAX
multivariate ARMAX models.
Kirchgässner G and J. Wolters, Introduction to Modern Time
Series Analysis, Springer-Verlag, Berlin, 2007
Brockwell, PJ and RA. Davis, Introduction to Time Series
and Forecasting, Springer-Verlag New York, Inc
McGrawHill, 2002
Shumway RH and DS Stoffer. Time Series Analysis and
Its Applications, Springer Science+Business Media, LLC,
2006
SM 092217: TEORI RESIKO DAN ANALISIS
KEPUTUSAN
(MATA KULIAH PILIHAN)
SM 092217: RISK THEORY AND DECISION ANALYSIS
(ASSORTED COURSE TITLE)
Kurikulum/Curriculum ITS : 2009-2014
x
x
x
x
x
x
x
x
Credits: 3 SKS / 3 Credit units
Semester: I
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
x
Mahasiswa mampu menerapkan matematika dalam
menganalisis resiko dalam setiap pengambilan keputusan.
x
Student able to apply mathematics to risk analysis on decision
making
KOMPETENSI/
x
Mampu mengikuti perkembangan Matematika, Sains dan
29
x
x
x
x
x
POKOK BAHASAN/
SUBJECTS
PUSTAKA UTAMA/
REFERENCES
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
MATA KULIAH/
COURSE TITLE
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
Resiko dan analisis keputusan
Risk and decision analysis
Proses analisis keputusan
Decision analysis process
Kebijakan keputusan
Decision policy
Utilitas dan keputusan multi kriteria
Utility and multicriteria decision
Pohon keputusan
Decision tree
Penetapan dan bias
Judgment and bias
Menghubungkan resiko
Relating risk
Stochastics variance
Chavas J.P, Risk Analysis in Theory and Practice, Elsevier Inc,
2004
John Schuyler, Risk and Decision Analysis in Projects, Project
Managemet Institute, Pennsylvania USA, 2001
Kurikulum/Curriculum ITS : 2009-2014
COMPETENCY
SM 092219: SISTEM FUZZY
(MATA KULIAH PILIHAN)
SM 092219: FUZZY SYSTEM
(ASSORTED COURSE TITLE)
Credits: 3 SKS / 3 Credit units
Semester: III
TUJUAN
PEMBELAJARAN/
x
Memberikan pengetahuan tentang kenapa sistem fuzzy,
matematika sistem fuzzy, operasi pada sistem fuzzy, relasi
fuzzy, variable linguistic, logika fuzzy, pengambilan
30
x
x
x
KOMPETENSI/
COMPETENCY
x
x
x
x
POKOK BAHASAN/
SUBJECTS
PUSTAKA UTAMA/
REFERENCES
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
keputusan fuzzy, dan forecasting-clustering fuzzy.
To give knowledges about why fuzzy system, operation on
fuzzy system, fuzzy relationship, fuzzy logic, fuzzy decision
making, and fuzzy clustering/forecasting.
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
Kenapa sistem fuzzy?
Why fuzzy system?
Matematika Himpunan Crsip vs Fuzzy
Mathematics Crisp vs Fuzzy Set
Fungsi keanggotaan
Membership function
Operasi-operasi pada himpunan fuzzy
Operation on Fuzzy Set
Variabellinguistic
Linguistic Variables
Relasi fuzzy, dan Logika Fuzzy
Fuzzy relation and fuzzy logic
Model-model pengambilan keputusan fuzzy
Models of fuzzy decision making
Forecasting dan clustering fuzzy
Fuzzy forcasting and clustering
Buckley J, and E. Eslami, An Introduction to Fuzzy Logic and
Fuzzy Sets, Physica Heidelberg, 2001,
Klir, GJ and B. Juan, Fuzzy Set and Fuzzy Logic, Prentice Hall, New
Jersey, 2001
Zimmerman H.J, Fuzzy Set Theory and Its Applications, Kluwer
Academic Publisher, 1996.
Zadeh, LA., Fuzzy Sets, Fuzzy Logic, and Fuzzy Systems: Selected
Papers , Kluwer Academic Publisher, 1996
Kurikulum/Curriculum ITS : 2009-2014
LEARNING
OBJECTIVES
31
MATA KULIAH/
COURSE TITLE
SM 092221: PENGOLAHAN CITRA
(MATA KULIAH PILIHAN)
SM 092221: IMAGE PROCESSING
(ASSORTED COURSE TITLE)
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
x
Mahasiswa mampu memahami konsep dasar dari pengolangan
citra digital dan menerapkannya ke aplikasi yang lebih kompleks
x
Students are able to comprehend basic concepts of digital
image processing and apply it to more complex application.
x
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
Konsep dasar dari pemrosesan citra
The basic steps of image processing
Elemen system DIP, model citra sederhana, kuantisasi dan
sampling
DIP system element, simple Image Model, quantization and
sampling,
Transformasi Fourier, transformasi Fourier Diskrit 2D
Fourier transformation, 2D Discrete Fourier Transforms
Manipulasi citra: model warna, manipulasi RGB, metode
frekuensi dan spasial
Image Manipulation: Color model, RGB manipulation, Frequency
and spatial method,
Transformasi geometri
Geometry Transforms,
Perbaikan citra
Image Enhancement,
x
KOMPETENSI/
COMPETENCY
x
x
x
x
x
x
x
x
POKOK BAHASAN/
SUBJECTS
x
x
x
x
x
x
x
x
Kurikulum/Curriculum ITS : 2009-2014
Credits: 3 SKS / 3 Credit units
Semester: I
32
PUSTAKA UTAMA/
REFERENCES
MATA KULIAH/
COURSE TITLE
x
Segmentasi citra
Image Segmentation,
Pengantar pola
Introduction to pattern,
Kompresi citra
Image compression.
Go Rafael C. Gonzalez and Richard E. Woods, Digital Image
Processing, Addison Wesley. 1993
Robert J. Schalkoff, Digital Image Processing and Computer
Vision, John Wiley and Son. 1999
Anil K. Jain, Fundamental of Digital Image Processing,
Prentice Hall, 1989
SM 092209: ANALISIS DATA SURVIVAL
(MATA KULIAH PILIHAN)
SM 092209: SURVIVAL DATA ANALYSIS
(ASSORTED COURSE TITLE)
Credits: 3 SKS / 3 Credit units
Semester: I
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
x
Mahasiswa mampu menganalisis data daya survive
dengan beberapa pendekatan model
x
Students are able to analyze survival data with some
model approach
x
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
x
KOMPETENSI/
COMPETENCY
x
x
x
x
Kurikulum/Curriculum ITS : 2009-2014
x
x
x
x
x
x
x
33
POKOK BAHASAN/
SUBJECTS
PUSTAKA UTAMA/
REFERENCES
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
MATA KULIAH/
COURSE TITLE
Pengantar analisis survival
Introduction to Survival Analysis
Kurva survival Kaplan-Meier dan Uji log rank
Kaplan–Meier Survival Curves and the Log–Rank Test .
Model bencana proporsional Cox dan karakteristiknya
The Cox Proportional Hazards Model and Its
Characteristics
Mengevaluasi bencana proporsional
Evaluating the Proportional Hazards
Prosedur berjenjang Cox
The Stratified Cox Procedure
Perluasan daribnecana proporsional Cox
Extension of the Cox Proportional Hazards
Model-model Survival Parametrik
Parametric Survival Models
Analisis Survival Kejadian berulang
Recurrent Event Survival Analysis
Komptensi Analisis resiko survival
Competing Risks Survival Analysis
Kleinbaum DG and M. Klein, Survival Analysis, Springer
Science+Business Media, Inc., 2005
Cox, D.R. and Oakes, D., Analysis of Survival Data,
Chapman&Hall, 1994,
Collect,D., Modelling Survival Data in Medical Research,
Chapman & Hall. 1996,
SM 092225: OPTIMASI HEURISTIK
(MATA KULIAH PILIHAN)
SM 092225: HEURISTICS OPTIMIZATION
(ASSORTED COURSE TITLE)
Kurikulum/Curriculum ITS : 2009-2014
x
x
x
x
x
x
Credits: 3 SKS / 3 Credit units
Semester: I
x
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
x
KOMPETENSI/
x
Mahasiswa mampu memahami metode-metode heuristik dan
mengimplementasikannya untuk menyelesaikan masalah
optimasi
Student are able to comprehend heuristics methods and
implement it to solve optimization problem
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
34
x
x
x
x
x
POKOK BAHASAN/
SUBJECTS
PUSTAKA UTAMA/
REFERENCES
MATA KULIAH/
COURSE TITLE
x
x
x
x
x
x
x
x
x
x
x
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
Simulated Annealling
Scatter Search
Tabu Search
Evolutionary Algorithms
Genetics Algorithms and Genetics Programming
Memetics Algorithms
Ant Colony Algorithms
Simulated Annealling
Petrowski J.D. and P.S.E. Taillard, Metaheuristics for Hard
Optimization, Springer-Verlag Berlin Heidelberg, 2006
Glover F. and Kochenberger G.A., Hand Book of
Metaheuristics, Kluwer Academic Publishers, 2003
Doerner K.F., Gendreau M., Greistorfer P., Gutjahr W.J,
Hartl RF. and M. Reimann KF , Metaheuristics Progress in
Complex Systems Optimization, Springer Science +
Business Media, LLC 2007
Kurikulum/Curriculum ITS : 2009-2014
COMPETENCY
SM 092227: OPTIMASI KOMBINATORIAL
(MATA KULIAH PILIHAN)
SM 092227: COMBINATORIC OPTIMIZATION
(ASSORTED COURSE TITLE)
Credits: 3 SKS / 3 Credit units
Semester: I
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
x
Memberikan pengetahuan kepada mahasiswa prinsip
matematika untuk memodelkan dan mengembangkan
penyelesaian optimal permasalahan combinatorial
x
To provide the student mathematical principles to modelling
and developing optimal solution combinatorial problems.
35
x
KOMPETENSI/
COMPETENCY
x
x
x
x
POKOK BAHASAN/
SUBJECTS
PUSTAKA UTAMA/
REFERENCES
x
x
x
x
x
x
x
x
x
x
x
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
Polytopes and Linear Programming
Matroids and Greedy Algorithm
Minimum-Weights Dipaths
Matroids Intersection
Matching
Networks Flow and Cuts
Cutting Planes for Integer Programming
Branch and Bound for discrete optimization
Optimizing Submodular Function
Jon Lee, A First Course in Combinatorial Optimization,
Cambride Text in Applied Mathematics - Cambride
University Press, 2004
Jens Gottlieb
and Günther R. Raidl, Evolutionary
Computation in Combinatorial Optimization, SpringerVerlag Berlin Heidelberg, 2006
Kurikulum/Curriculum ITS : 2009-2014
x
36
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
x
Menyiapkan mahasiswa pemahaman topic-topik saat ini
tentang riset operasi
x To provide the student with an understanding of the
current research topic in Operations Research
x
x
KOMPETENSI/
COMPETENCY
x
x
x
x
x
POKOK BAHASAN/
SUBJECTS
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
Tergantung kepada dosen pengampu, akan diinformasikan
kepada mahasiswa sebelum masa perkuliahan
Kurikulum/Curriculum ITS : 2009-2014
MATA KULIAH/
COURSE TITLE
SM 092229: KAPSEL OPERATIONS RESEARCH
(MATA KULIAH PILIHAN)
SM 092229: SELECTED TOPICS OF
OPERATIONS RESEARCH
(ASSORTED COURSE TITLE)
Credits: 3 sks / credits unit
Semester: III
Depend on the lecture, it will be informed to the student before
semester begin
PUSTAKA UTAMA/
REFERENCES
MATA KULIAH/
COURSE TITLE
SM 092231: GRID COMPUTING
(MATA KULIAH PILIHAN)
37
SM 092231: GRID COMPUTING
(ASSORTED COURSE TITLE)
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
x
Mahasiswa
mampu
mengimplementasikan
matematika menggunakan konsep grid computing.
komputasi
x
Student able to implemented mathematical
computation using grid computing concept
/numerical
x
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
x
KOMPETENSI/
COMPETENCY
x
x
x
x
POKOK BAHASAN/
SUBJECTS
PUSTAKA UTAMA/
REFERENCES
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Definisi grid komputing
Definition of grid computing
Manajemen data
Data management
Penjadwalan grid dan layanan informasi
Grid scheduling and information services
Keamanan dalam grid computing
Security in grid computing
Grid middleware
Grid middleware
Tinjauan arsitektur dari poyek grid
Architectural overview of grid project
Metode monte carlo
Monte Carlo method
Implementasi pada terapan persamaan differensial parsial
Implementation on applied partial differential equations
Magoules F, Pan J, Tan KA, and A. Kumar, Introduction to
Grid Computing, Chapman & Hall Book, 2009
Foster, I and Kasselman, The Grid 2, Elsevier, 2004
Kurikulum/Curriculum ITS : 2009-2014
Credits: 3 SKS / 3 Credit units
Semester: III
38
Credits: 3 SKS / 3 Credit units
Semester: III
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
x
Memberikan pengetahuan dalam melakukan eksplorasi data
besar untuk mendapatkan pola, trends, dan anomali-anomali
dengan model-model quantitative, merubah data menjadi
informasi dan merubah informasi menjadi pengetahuan.
x
Finding patterns, trends, and anomalies in these datasets, and
summarizing them with simple quantitative models. Turning
data into information and turning information into knowledge.
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
Data Mining and machine learning
Input: concepts, instances, and attributes
Output: Knowledge representation
statistical modelling,
decision tree,
association rules,
linear model,
x
x
KOMPETENSI/
COMPETENCY
x
x
x
x
POKOK BAHASAN/
SUBJECTS
x
x
x
x
x
x
x
Kurikulum/Curriculum ITS : 2009-2014
MATA KULIAH/
COURSE TITLE
SM 092233: DATA MINING DAN PENGENALAN
POLA
(MATA KULIAH PILIHAN)
SM 092233: DATA MINING AND PATTERN
RECOQNITION
(ASSORTED COURSE TITLE)
39
PUSTAKA UTAMA/
REFERENCES
x
x
MATA KULIAH/
COURSE TITLE
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
nearest neighbour,
clustering,
Bayesian networks,
Weitten I.A .and E.Frank, Data Mining: Practical Machine
Learning Tools and Techniques, Elsevier Inc, 2005
Ho Tu Bao, Introduction to Knowledge Discovery and Data
Mining, manuscript from Institute of Information
Technology, National Centre for Natural Science and
Technology, Taiwan, 2004
Dasu T. and T. Johnson , Exploratory Data Mining and
Data Cleaning, Johm Wiley & Sons, 2003
SM 092235: KAPSEL ILMU KOMPUTER
(MATA KULIAH PILIHAN)
SM 092235: SELECTED TOPICS OF
COMPUTER SCIENCES
(ASSORTED COURSE TITLE)
Credits: 3 sks / credits unit
Semester: III
x
Menyiapkan mahasiswa pemahaman topic-topik saat ini
tentang ilmu komputer
x To provide the student with an understanding of the
Kurikulum/Curriculum ITS : 2009-2014
x
x
x
x
current research topic in computer sciences
x
x
KOMPETENSI/
COMPETENCY
x
x
x
x
POKOK BAHASAN/
SUBJECTS
x
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
Tergantung kepada dosen pengampu, akan diinformasikan
kepada mahasiswa sebelum masa perkuliahan
40
Depend on the lecture, it will be informed to the student before
semester begin
MATA KULIAH/
COURSE TITLE
SM 092237: INVERS PROBLEM
(MATA KULIAH PILIHAN)
SM 092237: INVERSE PROBLEMS
(ASSORTED COURSE TITLE)
Credits: 3 SKS / 3 Credit units
Semester: III
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
x
Mahasisiwa mampu menyelesaikan masalah nyata dengan
menerapkan metode invers problem
x
Student able to solve real world problem using inverse problem
x
Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi
Able to follow development of Mathematics, science and
technology
Mampu mengembangkan Matematika dan Terapannya
Able to develop Mathematics and its applications
Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan
masalah nyata
Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving
x
KOMPETENSI/
COMPETENCY
x
x
x
x
POKOK BAHASAN/
SUBJECTS
x
x
x
x
x
x
x
x
x
Diskrit invers problem umum
The general discrete inverse problem
Metode monte carlo
Monte Carlo Method
Kriteria least square
The least square criterion
Kriteria nilai mutlak dan minimax
Least absolute value criterion and minimax criterion
Fungsional inverse problem
Kurikulum/Curriculum ITS : 2009-2014
PUSTAKA UTAMA/
REFERENCES
41
PUSTAKA UTAMA/
REFERENCES
x
x
MATA KULIAH/
COURSE TITLE
Functional inverse problem
Aplikasi invers problem
Aplication of inverse problem
Albert Tarantola, Inverse Problem Theory and Methods for
Model Parameter Estimation, Society for Industrial and
Apllied Mathematics (SIAM), 2005
Victor Isakov, Inverse Problem for Partial Differential
Equations, Springer Verlag Berlin, 1998
Aster A.C., Borchers B., and C.H. Thurber,
Parameter Estimation and Inverse Problem, Elsevier inc,
2005
SM 0912239: RISET OPERASI LANJUT
(MATA KULIAH PILIHAN)
SM 0912239: ADVANCED OPERATION
RESEARCH
(ASSORTED COURSE TITLE)
Credits: 3 sks / credits unit
Semester: 3
x Memberikan pemahaman kepada mahasiswa teori dan aplikasi
riset operasi untuk menyelesaikan masalah di industri
TUJUAN
PEMBELAJARAN/
LEARNING
OBJECTIVES
x To provide the student with an understanding of the theories
and applications of the operations research to solve a problem
at industries.
Kurikulum/Curriculum ITS : 2009-2014
x
x
x
x
x
KOMPETENSI/
COMPETENCY
POKOK BAHASAN/
SUBJECTS
x
x
x
x
x
x
x
x
x
Goal Programming,
Pemrograman multi objektif
Multi Objective Programming,
System antrean
Queuing system,
Teori permainan
Game theory,
simulasi
Simulation
42
PUSTAKA UTAMA/
REFERENCES
x
x
x
Pemrograman non linier
Nonlinear Programming.
Ravindran, A.R., Operations Research Methodologie, CRC Press,
2009.
Taha, H.A., Operation Research an Introductio, 7th Edition
Prentice Hall Pearson Education, Inc., New Jersey, 2003.
Hiller & Lieberman, Introduction to Operations Research,
Holden-Day Inc., California, 1996.
Winson, Operation Research Applications and Algorithm,
Duxbury Press Belmont, California, 1994.
Kurikulum/Curriculum ITS : 2009-2014
x
x
x
43