POSTGRADUATE PROGRAM (MAGISTER) Kompetensi Lulusan
[FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM] [FACULTY OF MATHEMATICS AND NATURAL SCIENCES]
Program Studi [JURUSAN MATEMATIKA] Department
[MATHEMATICS DEPARTMENT]
Jenjang Pendidikan PROGRAM PASCA SARJANA (MAGISTER) Programme
POSTGRADUATE PROGRAM (MAGISTER)
Kompetensi
x AKADEMISI DI BIDANG MATEMATIKA DAN TERAPANNYA
Lulusan
x PENELITI DI BIDANG MATEMATIKA DAN TERAPANNYA
Graduate
x ACADEMICIAN IN MATHEMATICS AND ITS APPLICATIONS
Competence
x RESEARCHER IN MATHEMATICS AND ITS APPLICATIONS
STRUKTUR KURIKULUM/COURSE STRUCTURE
No. Kode MK
sks Code
Nama Mata Kuliah (MK)
Course Title
Credits
ITS : 2009-2014
SEMESTER I
1 SM092301 Aljabar 3 Algebra 2 SM092303 Analisis Fungsional
3 rriculum
Cu
Functional Analysis
3 SM092305 Pemodelan Matematika dan Simulasi 3 Mathematical Modeling and Simulation 4 SM092307 Bioinformatika
3 Bioinformatics
12 Kurikulum/
Jumlah sks/Total of credits
SEMESTER II
1 SM092302 Komputasi Numerik 3 Numerical Computation
2 SM092304 Komputasi Jaringan Syaraf Tiruan 3 Artificial Neural Network Computation
3 Mata Kuliah Pilihan 4 SM092202 Optimasi Dinamis
3 Dynamics Optimazation 5 SM092204 Logistik dan Metode Perencanaan Transportasi
3 Logistics and Transportation Planning Method 6 SM092206 Teori dan Aplikasi Graf
3 Theory and Application of Graph 7 SM092208 Dispersi Atmosfir
3 Atmospheric Dispersion 8 SM092210 Kecerdasan Buatan
3 Artificial Intelegence
SEMESTER III
1 SM092201 Aljabar MaxPlus 3 MaxPlus Algebra 2 SM092203 Komputasi Dinamika Fluida
3 Computational Fluid Dynamics 3 SM092205 Kontrol Optimum
3 Optimum Control 4 SM092207 Kapita Selekta Pemodelan dan Simulasi
3 Special Topic of Modeling and Simulation 5 SM092209 Analisis Wavelet
3 Wavelet Analysis 6 SM092211 Kapita Selekta Analisis Terapan
3 Special Topic of Applied Analysis 7 SM092213 Multikriteria Optimum
3 Optimum Multicriterion 8 SM092215 Analisis Time Series
3 Time Series Analysis 9 SM092217 Teori Resiko dan Analisis Keputusan
3 Risk Theory and Decision Analysis 10 SM092219 Sistem Fuzzy
3 Fuzzy System 11 SM092221 Pengolahan Citra
3 ITS : 2009-2014
Image Processing 12 SM092223 Analisis Data Survival
3 Data Survival Analysis
rriculum
13 SM092225 Optimasi Heuristik
3 Cu
Heuristic Optimazation 14 SM092227 Optimasi Kombinatorial
3 Combinatorial Optimazation 15 SM092229 Kapita Selekta Riset Operasi
3 Special Topic of Operation Research
Kurikulum/
16 SM092231 Grid Computing 3 Grid Computing
17 SM092233 Data Mining dan Pengenalan Pola 3 Data Mining and Pattern Recognition
18 SM092235 Kapita Selekta Ilmu Komputer 3 Special Topic of Computer Science 19 SM092237 Invers Problem
3 Invers Problem 20 SM092239 Riset Operasi Lanjut
3 Advanced Operation Research
Jumlah sks/Total of credits
SEMESTER IV
1 SM092306 Tesis 6 Thesis
Jumlah sks/Total of credits
DEPARTMENT OF MATHEMATICS PROGRAM PASCASARJANA/MAGISTER PROGRAM SILABUS KURIKULUM/COURSE SYLLABUS
SM 092301: ALJABAR
(MATA KULIAH WAJIB)
MATA KULIAH/ SM 092301: ALGEBRA COURSE TITLE
(COMPULSARY COURSE TITLE)
Credits: 3 SKS / 3 Credit units Semester: I
TUJUAN
x Mahasiswa mampu memahami secara umum struktur
PEMBELAJARAN/
aljabar dan notasinya.
LEARNING
x The Students will be Understand to the generalize of the
OBJECTIVES
structures algebra and related notion. x Mahasiswa mampu menerapkan aljabar dalam matematika
dan masalah riil ITS : 2009-2014
KOMPETENSI/
x The students be able to apply algebra in the mathematics and real problems
COMPETENCY
x Mahasiswa mampu menganalisis struktur aljabar x The students able to analyze the structure algebra.
rriculum x Mahasiswa mampu menyusun contoh-contoh aplikasi
Cu x The studentds able to contruct some application exsamples
POKOK
x Grup dan semigrup
BAHASAN/
x Grup and Semigrup
SUBJECTS
x Field berhingga dan Polinomial Kurikulum/ x Finite field and Polynomial
Spindler K., Abstract Algebra With Applications, Volume I
PUSTAKA
Macmilan Marcel Dekker.Inc, 1994
UTAMA/
Spindler K., Abstract Algebra With Applications, Volume II Macmilan Marcel Dekker.Inc, 1994.
REFERENCES
Lidl R, and G. Pliz, Applied Abstract Algebra: Second Edition, Spinger Verlag, 1998. x Subiono, Aljabar, buku ajar Matematika FMIPA ITS, 2009
SM 092303 ANALISIS FUNGSIONAL MATA KULIAH/ SM 092303 FUNCTIONAL ANALYSIS COURSE TITLE
Credits: 3 sks / credits unit Semester: 1
Mahasiswa mampu menggunakan analisa secara matematis,
TUJUAN
menelaah suatu teorema serta menerapkannya pada masalah
PEMBELAJARAN/
dalam bidang matematika dan bidang lainnya.
LEARNING
The students can do mathematical analysis, study and describe the OBJECTIVES thoerems and also aplly those thoerems in mathematical field and
others
x Mahasiswa dapat menjelaskan sifat-sifat ruang vektor, ruang ITS : 2009-2014 metrik, ruang normsifat-sifat himpunan, dan sifat-sifat barisan
pada ruang-ruang tersebut x Mahasiswa dapat menjelaskan sifat-sifat ruang hasil kali dalam,
rriculum ortogonalitas vektor dan barisan ortonormal beserta
Cu penggunaanya
x Mahasiswa dapat menerapkan titik tetap Banach untuk menyelesaikan masalah persamaan linear, persamaan diferensial dan persamaan integral dan teorema approksimasi pada ruang norm
Kurikulum/
KOMPETENSI/
Mahasiswa mengerti dan mampu menggunakan teorema spektral
COMPETENCY
dan kaitannya dengan nilai eigen.
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,
SUBJECTS
konvergensi barisan, barisan Cauchy x Ruang norm, ruang Banach, ruang norm dimensi hingga,
operator linear, operator terbatas x Ruang hasil kali dalam, ruang Hilbert, ortogonal dan komplemen
ortogonal, himpunan dan barisan ortonormal x Teorema Hahn-Banach, dan terapannya pada operator linear
terbatas x Teorema titik tetap Banach dan terapannya pada persamaan
linear, persamaan diferensial, persamaan integral x Teori Approksimasi pada ruang norm, ketunggalan aproksimasi,
aproksimasi seragam x Teori spektral dari operatro linear pada ruang norm untuk
dimensi hingga dan operator linear terbatas.
x Vector space, metric space, open and closed set, convergence of sequences, Cauchy sequence
x Norm space, Banach space, finite dimensional of norm space, linear operator, bounded operator
x Inner product space, Hilbert space, ortogonal and complement ortogonal, ortonormal set and sequences
x Hanh-Banach theorem and its application in bounded linear ITS : 2009-2014 operator
x Banach Fixed point theorem and its application to linear differential and integral equation
rriculum x Approximation theory in norm space, uniqueness, uniform
Cu approximation
x Spectral theory of linear operator in norm space, in finite dimension and bounded operator
Kurikulum/
PUSTAKA UTAMA/
x KREYSZIG, E., INTRODUCTION FUNCTIONAL ANALYSIS WITH APPLICATION, 1978, JOHN WILEY & SONS
REFERENCES
x ZEIDLER, E., APPLIED FUNCTIONAL ANALYSIS, 1995, SPRINGER VERLAG
MATA KULIAH/
SM 092305: PEMODELAN MATEMATIKA DAN
COURSE TITLE
SIMULASI
(MATA KULIAH WAJIB) SM 092305: MATHEMATICAL MODELING AND SIMULATION
(COMPULSARY COURSE TITLE)
Credits: 3 SKS / 3 Credit units
Semester: I
x Mata kuliah ini membahas tentang metode atau teknik untuk
TUJUAN
mengkonstruksi model matematika dari fenomena yang akan
PEMBELAJARAN/
dikaji menggunakan hukum-hukum yang mengendalikan
LEARNING
fenomena tersebut
OBJECTIVES x
This course describes either method or technique to construct mathematical model of a considered phenomenon using a governed law of the phenomenon.
x Mampu mengikuti perkembangan Matematika, Sains dan Teknologi
ITS : 2009-2014 x Able to follow development of Mathematics, science and
technology
KOMPETENSI/
x Mampu mengembangkan Matematika dan Terapannya
COMPETENCY
x Able to develop Mathematics and its applications
rriculum x Mampu mengimplementasikan kerangka berfikir matematis
Cu 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 Kurikulum/ x Konsep dasar pemodelan matematika
x Basic concept of mathematical modeling x Pendekatan pembentukan model : eksplorasi data dan
konfirmasi data
POKOK BAHASAN/
x Structuring model approach: data exploratory dan data
SUBJECTS
confirmatory x Pemodelan matematika lanjut x Advanced mathematical modeling
x Contoh-contoh pemodelan matematika lanjut x Examples of Advanced mathematical modeling
PUSTAKA UTAMA/
x Bellomo, N. dan Preziosi, L., Modelling Mathematical Methods
and Scientific Computing, Italy: CRC Press, 1995
REFERENCES
x Beltrami, E., Mathematical for Dynamic Modelling, New York, USA: Academic Press,1987 x Beltrami, E., Mathematical for Dynamic Modelling, New York, USA: Academic Press,1987
x Johansson, R., System Modelling and Identification, New York, USA: Prentice Hall International, 1993.
SM 092307: BIOINFORMATIKA (MATA KULIAH WAJIB)
MATA KULIAH/ SM 092307: BIOINFORMATICS COURSE TITLE
(COMPULSARY COURSE TITLE)
Credits: 3 SKS / 3 Credit units
Semester: I
TUJUAN
x Mata kuliah ini membahas tentang metode matematika dan
PEMBELAJARAN/
software tools yang digunakan untuk memodelkan, ITS : 2009-2014 mensimulasikan dan memprediksi fungsi DNA.
LEARNING
x This course discuss about mathematical method and software OBJECTIVES tools which used for modeling, simulate, and prediction of DNA
rriculum function. Cu
x Mampu mengikuti perkembangan Matematika, Sains dan Teknologi
x Able to follow development of Mathematics, science and technology
KOMPETENSI/
x Mampu mengembangkan Matematika dan Terapannya Kurikulum/
COMPETENCY
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 Metode Matematika untuk pemodelan DNA x Mathematical methods for DNA modeling. x Metode komputasi lunak untuk pemodelan DNA
POKOK BAHASAN/
x Soft computing for DNA modeling
SUBJECTS
x Konsep dasar biologi molekuler dan data bioinformatics x Basic concept of biology molecular and data bioinformatics x Pengenalan tools bioinformatics x Introduction of bioinformatica tools x Komparasi sequence x Konsep dasar biologi molekuler dan data bioinformatics x Basic concept of biology molecular and data bioinformatics x Pengenalan tools bioinformatics x Introduction of bioinformatica tools x Komparasi sequence
PUSTAKA UTAMA/
x Shen, SN and JA TuZynski, Theory and Mathematical Methods
REFERENCES
for Bioinformatics, Springer Inc, 2008 x
Christianini N and MW. Hahn, Computational Genomics, Cambridge University Press, 2006
SM 092302: KOMPUTASI NUMERIK (MATA KULIAH WAJIB)
MATA KULIAH/ SM 092302: NUMERICAL COMPUTATION COURSE TITLE
(COMPULSARY COURSE TITLE)
Credits: 3 SKS / 3 Credit units Semester: II ITS : 2009-2014
x Matakuliah komputasi numerik ini menjelaskan metode rriculum
TUJUAN
penyelesaian numerik dari persamaan differensial biasa Cu
PEMBELAJARAN/
dan/atau parsial menggunakan metode beda hingga, elemen hingga dan volume hingga dengan bantuan komputer
LEARNING
x This course describes numerical solution method of both/either OBJECTIVES ordinary differential equation(ODE) and/or partial differential equation(PDE)using the methods of finite difference, finite
Kurikulum/
element and finite volume with computer
x Mampu mengikuti perkembangan Matematika, Sains dan Teknologi
x Able to follow development of Mathematics, science and technology
KOMPETENSI/
x Mampu mengembangkan Matematika dan Terapannya
COMPETENCY
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
POKOK BAHASAN/
x Masalah Nilai awal dari PD Biasa
SUBJECTS
x Initial Value Problem of ODE x Masalah Nilai Batas dari PD Parsial x Initial Value Problem of ODE x Masalah Nilai Batas dari PD Parsial
x Hunter, P., FEM/BEM, New Zealand: Dept. of Engineering Sciences, Auckland University, 2007
x Mitchell, A.R & Griffith, D.F., The Finite Difference Method in
PUSTAKA UTAMA/
Partial Diffrential Equations, New York: A Wiley- Interscience
REFERENCES
Publication (John Wiley & Sons) , 1980 x Griffiths, D.V. dan Smith, I.A., Numerical Methods for Engineers,
London: Blackwell Scientific Publications, 1991
x Whye-Teong Ang, A Beginner's Course in Boundary Element Methods, New York: 2007
ITS : 2009-2014
rriculum Cu
SM 092305: KOMPUTASI JARINGAN
Kurikulum/
SYARAF TIRUAN (MATA KULIAH WAJIB)
MATA KULIAH/ SM 092305: COMPUTATION OF ARTIFICIAL COURSE TITLE
NEURAL NETWORKS
(COMPULSARY COURSE TITLE)
Credits: 3 SKS / 3 Credit units
Semester: II
TUJUAN
x Matakuliah komputasi jaringan syaraf tiruan menjelaskan
PEMBELAJARAN/
algoritma-algoritma yang dipakai untuk memodelkan data dengan bantuan komputer. Mahasiswa mampu
LEARNING
menterjemahkan langsung algoritma menjadi program 9
OBJECTIVES 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
KOMPETENSI/
x Mampu mengembangkan Matematika dan Terapannya
COMPETENCY
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
ITS : 2009-2014 x Review computer programming x Masalah klasifikasi sederhana menggunakan perceptron, hebb
dan adaline rriculum x Simple classification problems using perceptron, heb, and adaline
Cu x Metode pengenalan pola menggunakan Hebb, Associative Memory, BAM, dan MLP
POKOK BAHASAN/
x Pattern recognition methods using Hebb, Associative Memory, BAM, and MLP
SUBJECTS
x Metode klasifikasi menggunakan MLP, RBF, jaringan recurrent, Kurikulum/
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
PUSTAKA UTAMA/
Jersey, USA, 1994.
REFERENCES
x Hassoum, MH, Fundamental of Artificial Neural Networks, MIT, 1995.
x Bishop, C, Neural Networks for Pattern Recoqnitions, Oxford
University Press, 1996 x Duda, RO, Hart, PE, Stork, DG, Pattern Classification, John Wiley
and Sons, 2001 x
Stork, DG and E. Yom-Tov, Computer Manual in MATLAB to Accompany Pattern Classification, Second Edition (Paperback), John Wiley and Sons, 2004
SM 092202: OPTIMASI DINAMIS
(MATA KULIAH PILIHAN)
MATA KULIAH/ SM 092202: DYNAMICS OPTIMIZATION COURSE TITLE
(ASSORTED COURSE TITLE)
Credits: 3 sks / credits unit Semester: II
ITS : 2009-2014
TUJUAN
x Memberikan pemahaman kepada mahasiswa tentang
PEMBELAJARAN/
optimisasi dan aplikasinya
LEARNING
x To provide the student with an understanding of the rriculum OBJECTIVES optimization and their applications Cu
x Mampu mengikuti perkembangan Matematika, Sains dan Teknologi
x Able to follow development of Mathematics, science and Kurikulum/ technology
KOMPETENSI/
x Mampu mengembangkan Matematika dan Terapannya
COMPETENCY
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 Pengantar desain
POKOK BAHASAN/
x Introduction to Design, Perumusan Masalah desain opt8imum
x x Optimum Design Problem Formulation, x Metode optimasi grafis x Graphical Optimization Method,
SUBJECTS SUBJECTS
PUSTAKA UTAMA/
Arora, J.S. Introduction to Optimum Design , Elsevier Academics
REFERENCES
Press, 2004. Bryson, A.E., Dynamics Optimizatio, Wiley , 2000
SM 092204: LOGISTIK DAN METODE PERENCANAAN TRANSPORTASI (MATA KULIAH PILIHAN)
ITS : 2009-2014
MATA KULIAH/
SM 092204: LOGISTIC AND TRANSPORTATION
COURSE TITLE
PLANNING METHODS
rriculum
Cu Credits: 3 SKS / 3 Credit units
(ASSORTED COURSE TITLE)
Semester: II
Kurikulum/ x Kuliah ini mendiskusikan tentang penjadwalan proyek,
penjadwalan job-shop, penjadwalan sistem asemble
TUJUAN
fleksibel, penjadwalan lot economis, perencanaan dan
PEMBELAJARAN/
penjadwalan dalam transportasi. The course discuss about project scheduling, job shop
LEARNING
x scheduling, scheduling of flexible assembly systems,
OBJECTIVES 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
x Mampu mengikuti perkembangan Matematika, Sains dan
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 mengembangkan Matematika dan Terapannya x Able to develop Mathematics and its applications
x Able to implement the framework of mathematically mind to design, analyze and evaluate real problem solving
x Pengantar sistem logistic x Introduction of logistics system x Meramalkan kebutuhan logistic x Forecasting logistics demand x Merencanakan jaringan logistic
POKOK BAHASAN/
x Planning logistics networks
SUBJECTS
x Menyelesaikan masalah manajemen persediaan x Solving inventory management problem x Merancang dan mengoperasikan gudang x Design and operating a warehouse x Merancang dan mengatur angkutan transportasi jarak dekat dan
jauh x Design and manage short/long haul transportation
x Ghiani, G, Laporte, G and R. Musmanno, An Introduction to
PUSTAKA UTAMA/
Logistics Systems Planning and Control , John Wiley and Sons, ITS : 2009-2014
REFERENCES
Ltd, 2004 x
Pinedo, ML, Planning and Scheduling in Manufacturing and Services, Springer Science, 2005
rriculum Cu
SM 092206 TEORI DAN APLIKASI GRAF
Kurikulum/
(MATA KULIAH PILIHAN)
MATA KULIAH/ SM 092206 GRAPH THEORY AND APPLICATIONS COURSE TITLE
(MATA KULIAH PILIHAN)
Credits: 3 SKS / 3 Credit units
Semester: II
TUJUAN
Agar memahami graph sebagai salah satu model matematika yang
PEMBELAJARAN/
sangat penting untuk berbagai masalah.
LEARNING
To provide the student with an understanding of the graph theory as OBJECTIVES a mathematical model for solving mathematical problem
KOMPETENSI/ COMPETENCY
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
POKOK BAHASAN/
(pewarnaan titik, pewarnaan sisi), masalah perjodohan, graph
SUBJECTS
bipartite, graph berarah (turnamen, alur lalu lintas, network). Introduction, graph tree, shortest distance problem, planar graph,
Euler graph, Hamilton graph, Colouring graph, matching problem, bipartite graph, directed graph.
F. Hanary, ”Graph Theory”, Addison-Wesley Publishing Co Inc., Massachussets USA, 1969
PUSTAKA UTAMA/
Deo Narscyh, “Graph Theory with Applications to
REFERENCES
Engineering and computer science Preslitice Hall Inc., Englewod Cliffs, N.J., USA
I Ketut Budayasa, “Teori Graph and Aplikasinya”, Unesa ITS : 2009-2014
University Press, 2007
rriculum Cu
SM 092208: DISPERSI ATMOSFIR (MATA KULIAH PILIHAN)
Kurikulum/
MATA KULIAH/ SM 092208: ATMOSPHERIC DISPERSION COURSE TITLE
(ASSORTED COURSE TITLE)
Credits: 3 SKS / 3 Credit units
Semester: II
TUJUAN
x Memberikan wawasan tentang teori dispersi atmosfir dan
PEMBELAJARAN/
menjelaskan tentang prinsip-prinsip dasar tentang pemodelan dispersi atmosfir
LEARNING
x To give an introduction to the theory of atmospheric OBJECTIVES dispersion and to describe the basic principles of
atmospheric dispersion modelling
KOMPETENSI/
x Mampu mengikuti perkembangan Matematika, Sains dan Teknologi
COMPETENCY
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 Pengangkutan skalar pada Atmosfir x Scalar Transport in the Atmosphere x Proses-proses pengangkutan x Transport Processes x Lapisan batas atmosfir x The Atmospheric Boundary Layer x Sumber-sumber titik penghasil polutan yang kontinyu x Continuous Point Sources of Pollutant
POKOK BAHASAN/
x Dispersi pada lingkungan nyata
SUBJECTS
x Dispersion in Real Environments x Kepulan Asap Gauss dari cerobong yang tinggi x Gaussian Plumes from High Chimneys
ITS : 2009-2014 x Deposisi x Deposition x Tipe-tipe dari model dispersi atmosfir
rriculum x Types of Atmospheric Dispersion Models
x Reaksi-reaksi kimiawi dari polutan yang ada di atmosfir Cu
x Chemical Reaction of Atmospheric Pollutants x Pembaganan pada Penyelesaian Numerik x Numerical Schemes x Barrat, R., Atmospheric Dispersion Modelling, 1st Edition,
Kurikulum/ Earthscan Publications, 2001
x Colls, J., Air Pollution, 1st Edition, Spon Press (UK), 2002 x European Process Safety Centre, Atmospheric Dispersion, 1st
PUSTAKA UTAMA/
Edition, Rugby: Institution of Chemical Engineers, 1999
REFERENCES
x Schnelle, K.B. and Dey, P.R., Atmospheric Dispersion Modeling Compliance Guide, 1st Edition, McGraw-Hill Professional, 1999
x Turner, D.B., Workbook of Atmospheric Dispersion Estimates: An Introduction to Dispersion Modeling, 2nd Edition, CRC Press,
1994 x
Zannetti, P., Air pollution modeling : theories, computational methods, and available software, Van Nostrand Reinhold, 1990
SM 092210: KECERDASAN BUATAN
(MATA KULIAH PILIHAN)
MATA KULIAH/ SM 092210: ARTIFICIAL INTELLIGENCE COURSE TITLE
(ASSORTED COURSE TITLE)
Credits: 3 SKS / 3 Credit units Semester: III
x Matakuliah kecerdasan buatan mendiskusikan metode merubah komputer menjadi cerdas yang mampu bernalar sebaik manusia. Dalam kuliah ini mahasiswa dituntut untuk bisa
TUJUAN
mengimplementasikan beberapa metode agar komputer bisa
PEMBELAJARAN/
menjadi cerdas dan bisa menyelesaikan suatu masalah yang
LEARNING
membutuhkan kecerdasan dalam menyelesaikanya. OBJECTIVES x 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.
ITS : 2009-2014 x Mampu mengikuti perkembangan Matematika, Sains dan
Teknologi x Able to follow development of Mathematics, science and
rriculum technology
Cu
KOMPETENSI/
x Mampu mengembangkan Matematika dan Terapannya
COMPETENCY
x Able to develop Mathematics and its applications x Mampu mengimplementasikan kerangka berfikir matematis
untuk merancang, menganalisis, dan mengevaluasi pemecahan Kurikulum/ masalah nyata
x Able to implement the framework of mathematically mind to design, analyze and evaluate real problem solving
konsep kecerdasan buatan,
concept of artificial intelligence
x teknik penyelesaian masalah menggunakan kecerdasan buatan x
problem-solver technique using artificial intelligence
POKOK BAHASAN/
x teknik pencarian, representasi pengetahuan, ketidakpastian searching technique, knowledge representation, uncertainty
SUBJECTS
xx
sistem pakar, and sistem pakar fuzzy
expert system and fuzzy expert system
x algoritma genetika dan pemrograman genetika x
genetics algorithms and genetic programming
x particle swarm optimization dan algoritma koloni semut x
particle swarm optimization and ant koloni algorithms particle swarm optimization and ant koloni algorithms
PUSTAKA UTAMA/
Modern Approach, McGrawHill, 2003
REFERENCES
x Eleane Rich and Kevin Knight, Artificial Intelligence, McGrawHill, 2000
x John Durkin, Expert Systems: design and development, Prentice Hall, 2003
SM 092212: MATEMATIKA SISTEM
(MATA KULIAH PILIHAN)
MATA KULIAH/ SM 092212: MATEMATICAL SYSTEM COURSE TITLE
(ASSORTED COURSE TITLE)
Credits: 3 SKS / 3 Credit units Semester: II
TUJUAN
x Mahasiswa mengerti secara umum matematika sistem dan
PEMBELAJARAN/
notasi yang berhubungan, teori ruang keadaan, keterkontrolan dan stabilitas
ITS : 2009-2014
LEARNING
x The Students understand to the generalize of matematical system and relate notion, the State Space Theory,
OBJECTIVES
controlability and the Stability x Mahasiswa bisa menggunakan hukum konservasi, prinsip-
rriculum prinsip fenomena dan fisika untuk membuat model
Cu matematika dari sistem
x The Students can use conservation laws, phenomenological and physical principles to make mathematical models of systems
Kurikulum/ x Mahasiswa mampu melinierisasi dari sistem nonlinear dan
menyelesaikan sistem differensial linier x The Students able to linearize of non linear system and
KOMPETENSI/
solve linear differential systems.
COMPETENCY
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 x The students able to apply controllability of system to stabilize the systems
x The students able to determine the stability criteria of the systems
x Model-model matematika
POKOK BAHASAN/
x Mathematical Models
SUBJECTS
x Pengantar teori ruang keadaan x Introduction to State Space Theory x Teori stabilitas x Stability Theory x Subiono, Matematika Sistem, Versi 2.0, buku ajar Jurusan
Matematika FMIPA-ITS, 2010.
PUSTAKA UTAMA/
x Olsder G.j. and J.W. van der Woude, “Mathematical Systems Theory”, Delft Uitgavers Maatschappij, 1994.
REFERENCES
x Hinrichsen D. and T. Pritchard “ Mathematical Systems Theory I Modelling, State Space Analysis, Stability and Robustness”, Springer Verlag ,2004
ITS : 2009-2014
SM 092214 ASIMILASI DATA MATA KULIAH/ SM 092214 DATA ASSIMILATION COURSE TITLE
Credits: 3 sks / credits unit rriculum Cu
Semester: 2
Mahasiswa mengerti dan mampu menerapkan berbagai algoritma
TUJUAN
dalam asimilasi data pada masalah identifikasi parameter dan Kurikulum/
PEMBELAJARAN/
estimasi variable keadaan dari system dinamik stokastik.
LEARNING
The students understand and can apply the algorithms of data OBJECTIVES 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
KOMPETENSI/
perkembangan metode asimilasi data.
COMPETENCY
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.
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.
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
POKOK BAHASAN/
filter
Studi kasus penerapan asimilasi data
SUBJECTS
x Data assimilation: forecasting, modeling, observations, sensitivity analysis
Modeling in data assimilation
x Some of data assimilation methods: stochastic static model, ITS : 2009-2014 deterministic dynamic model, stochastic dynamic model x
The advantage of Kalman filter: extended Kalman filter, RRSQRT filter, Ensemble Kalman Filter, Hibrid filter
rriculum x
Case studies
Cu
x LEWIS, J.M., LAKSHMIVARAHAN, DHALL, S.K., 2006, DYNAMIC
PUSTAKA UTAMA/
DATA ASSIMILATION: A LEAST SQUARES APPROACH,
REFERENCES
CAMBRIDE
x KALNAY, 2003, ATMOSPHERIC MODELING, DATA Kurikulum/
ASSIMILATION AND PREDICTABILITY, CAMBRIDGE SM 092201: ALJABAR MAX PLUS
(MATA KULIAH PILIHAN)
MATA KULIAH/ SM 092201: MAX PLUS ALGEBRA COURSE TITLE
(ASSORTED COURSE TITLE)
Credits: 3 SKS / 3 Credit units Semester: III
TUJUAN
x Mahasiswa mengerti secara umum aljabar max plus dan
PEMBELAJARAN/
notasinya, teori spektral, perilaku kualitatif periodik dan asimtotik, dan vektor siklus waktu.
LEARNING
OBJECTIVES 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.
x Mahasiswa mampu menerapkan aljabar maxplus di masalah nyata
x The Students be able to apply max-plus algebra in the real problems
KOMPETENSI/
x Mahasiswa mampu mampu mendapatkan nilai eigen dan vektor eigen dari matriks-matriks irreducible dan reducible
COMPETENCY
x The students able to find eigenvalues and eigenvectors of irreducible an reducible matrices.
x Mahasiswa mampu menganalisis perilaku periodik dari model linier max-plus
x The students able to analyze the periodic behavior of the max plus linear model.
x Aljabar Max-Plus x Max-Plus Algebra x Teori Spektral x Spectral Theory x Perilaku periodik dan vektor siklus waktu
ITS : 2009-2014
POKOK BAHASAN/
x Periodic behavior and the cycle-time vector
SUBJECTS
x Perilaku kualitatif asimtotik x Asympotic Qualitative Behavior
rriculum x Prosedur numerik dari nilai eigen matriks irreducible dan reducible
Cu x Numerical Procedure of eigenvalues of irreducible and
reducible matrices x Introduction to Petri Nets x Subiono, Aljabar Max-Plus, buku ajar Jurusan Matematika
Kurikulum/ FMIPA-ITS, 2010.
x 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,
PUSTAKA UTAMA/
Princeton University Press, 2006
REFERENCES
x 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
SM 092203: KOMPUTASI DINAMIKA FLUIDA (MATA KULIAH PILIHAN) SM 092203: COMPUTATIONAL FLUID DYNAMICS
MATA KULIAH/ COURSE TITLE
(CFD)
(ASSORTED COURSE TITLE)
Credits: 3 SKS / 3 Credit units Semester: III
x Matakuliah komputasi dinamika fluida ini membahas tentang
TUJUAN
penggunaan komputer dan teknik numerik untuk
PEMBELAJARAN/
menyelesaikan permasalahan yang berkaitan dengan aliran
LEARNING
fluida OBJECTIVES x The computational fluid dynamics course describes the
use of computers and numerical techniques to solve problems involving fluid flow
x Mampu mengikuti perkembangan Matematika, Sains dan Teknologi
x Able to follow development of Mathematics, science and technology
ITS : 2009-2014
KOMPETENSI/
x Mampu mengembangkan Matematika dan Terapannya
COMPETENCY
x Able to develop Mathematics and its applications x Mampu mengimplementasikan kerangka berfikir matematis
rriculum untuk merancang, menganalisis, dan mengevaluasi pemecahan
Cu masalah nyata x Able to implement the framework of mathematically mind to
design, analyze and evaluate real problem solving x
Persamaan aliran fluida Kurikulum/ x
Fluid flow equation x
Persamaan Pengangkutan Skalar
POKOK BAHASAN/
x Scalar transport equation
SUBJECTS
x Persamaan momentum x
Momentum equation x
Turbulen x
Turbulence Turbulence
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
x Hoffmann, K. A. and Chiang, S. T., Computational Fluid Dynamics For Engineers, Wichita, USA: Engineering Education System,
1995 x Chung, T.J., Computational Fluid Dynamics, Cambridge:
Cambridge University Press, 2002 x Welty, J.R., et al., Fundamentals of Momentum, Heat and Mass
PUSTAKA UTAMA/
Transfer, 3 rd Edition, New York, USA: John Wiley & Sons, Inc.,
REFERENCES
1995 x Versteeg, H.K. and Malalasekera, W., An Introduction to
ITS : 2009-2014 2007.
Computational Fluid Dynamics – The Finite Volume Method, Second Edition, England: Prentice Hall - Pearson Education Ltd.,
x Tu, J.Y., Yeoh, G.H. and Liu, G.Q., Computational Fluid Dynamics-
A Practical Approach, Oxford, UK: Butterworth-Heinemann rriculum Publications, 2008
Cu x
Yeoh, G.H. and Yuen, K.K., Computational Fluid Dynamics in Fire Engineering, Oxford, UK: Butterworth- Heinemann Publications, 2009
Kurikulum/
SM 092205: KONTROL OPTIMUM
(MATA KULIAH PILIHAN)
MATA KULIAH/ SM 092205: OPTIMAL CONTROL COURSE TITLE
(ASSORTED COURSE TITLE)
Credits: 3 sks / credits unit Semester: 3
TUJUAN
x Memberikan kepada mahasiswa pemahaman tentang masalah
PEMBELAJARAN/
control optimal, pemodelan, aplikasi, simulasi dan komputasi
LEARNING
OBJECTIVES 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 x Able to follow development of Mathematics, science and
technology
KOMPETENSI/
x Mampu mengembangkan Matematika dan Terapannya
COMPETENCY
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
Review kalkulus variasi
Review calculus of variation,
x Kontrol optimal: system waktu diskrit dan system waktu ITS : 2009-2014
kontinyu
x optimal control: Discrete-time systems and continuous- time systems,
rriculum
x Kontrol optimal terkendala dan tak terkendala Cu unconstrained and constrained optimal control,
POKOK BAHASAN/
xx
SUBJECTS
waktu akhir tetap dan bebas
fixed and free final time,
Kurikulum/ x
Aplikasi dan simulasi
application and simulation,
metode langung dan tak langsung
direct and indirect method,
Komputasi control optimal
computational optimal control .
1. Subchan, S and Zbikowski, R., Computational Optimal Control: Tools and Practice, Wiley, 2009.
2. Lewis, F. dan Syrmos Vassilis, Optimal Control, John
PUSTAKA UTAMA/
Wiley & Sons, Singapore, 1995.
REFERENCES
x Kamien, ML and Schwartz, N.L., Dynamic Optimizatio, North-Holland, Amsterdam, 1993.
x Lewis F., Optimal Estimation, John Wiley & Sons, Singapore, 1986.
SM 092207: KAPSEL PEMODELAN DAN SIMULASI (MATA KULIAH PILIHAN) MATA KULIAH/ SM 092207: SELECTED TOPICS OF COURSE TITLE MODELING AND SIMULATION (ASSORTED COURSE TITLE)
Credits: 3 sks / credits unit Semester: III
TUJUAN
x Menyiapkan mahasiswa pemahaman topic-topik saat ini tentang
PEMBELAJARAN/
pemodelan dan simulasi
LEARNING
ITS : 2009-2014 OBJECTIVES x To provide the student with an understanding of the current
research topic in modelling and simulation x Mampu mengikuti perkembangan Matematika, Sains dan
rriculum Teknologi
Cu x Able to follow development of Mathematics, science and
technology
KOMPETENSI/
x Mampu mengembangkan Matematika dan Terapannya
COMPETENCY
x Able to develop Mathematics and its applications
Kurikulum/ 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 Tergantung kepada dosen pengampu, akan diinformasikan
POKOK BAHASAN/
kepada mahasiswa sebelum masa perkuliahan
SUBJECTS
Depend on the lecture, it will be informed to the student before semester begin
PUSTAKA UTAMA/ REFERENCES
SM 092303 ANALISIS FUNGSIONAL SM 092303 FUNCTIONAL ANALYSIS MATA KULIAH/ COURSE TITLE
Kredit: 3 sks Credits: 3 credits unit Semester: I
Diharapkan mahasiswa mendapat pengetahuan dan pemahaman tentang pokok-pokok analisis fungsional, khususnya tentang ruang
TUJUAN
Banach, ruang Hilbert, dan operator linear kompak, serta mengenal
After completing this course, the students should have knowledge OBJECTIVES and comprehension of fundamental concept of functional analysis,
especially about Banach spaces, Hilbert spaces, and compact linear operators, and be acquainted to their applications.
ITS : 2009-2014 x Dapat mengenali ruang Banach dan ruang Hilbert, berserta sifat-
sifat utamanya. rriculum x Dapat menunjukkan sifat-sifat operator linear terbatas, operator
Cu kompak, dan dapat membuktikan sifat-sifat utama operator
kompak. x Dapat membuktikan kelengkapan ruang L p , dan mengenal
Kurikulum/ 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 L p spaces, and understand their applications.
x Ruang Banach dan ruang Hilbert: pelengkapan, operator terbatas, jumlahan langsung, basis ortonormal, jumlahan ortogonal.
POKOK BAHASAN/
x Operator-operator kompak: definisi dan sifat-sifat pokok, teorema spektral untuk operator simetrik kompak.
SUBJECTS
x Integrasi Lebesgue: fungsi terukur, integral Lebesgue, pengertian “hampir dimana-mana”, ruang Lebesgue L p , kelengkapan ruang L p .
x Dual dari L p : dekomposisi ukuran, ukuran kompleks, dual dari L p x Dual dari L p : dekomposisi ukuran, ukuran kompleks, dual dari L p
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 L p ,
completeness of L p . x The dual of L p : decomposition of measure, complex measure, the
dual of L p .
PUSTAKA UTAMA/
x Zeidler, E., “Applied Functional Analysis, Application to
Mathematical Physics”, Springer-Verlag, New York, 1995.
REFERENCES
Conway, J. B., “A Course in Functional Analysis”, Graudate Text in Mathematics, 96, Springer-Verlag, New York, 1990.
ITS : 2009-2014
SM 092211: KAPSEL ANALISIS TERAPAN
(MATA KULIAH PILIHAN)
SM 092211: SELECTED TOPICS OF
rriculum
MATA KULIAH/
Cu
APPLIED ANALYSIS (ASSORTED COURSE TITLE) COURSE TITLE
Credits: 3 sks / credits unit Semester: III
Kurikulum/
TUJUAN
x Menyiapkan mahasiswa pemahaman topic-topik saat ini
PEMBELAJARAN/
tentang pemodelan dan simulasi
LEARNING
OBJECTIVES 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
KOMPETENSI/
x Able to follow development of Mathematics, science and
COMPETENCY
technology x Mampu mengembangkan Matematika dan Terapannya x Able to develop Mathematics and its applications
x Mampu mengimplementasikan kerangka berfikir matematis x Mampu mengimplementasikan kerangka berfikir matematis
x Able to implement the framework of mathematically mind to design, analyze and evaluate real problem solving
x Tergantung kepada dosen pengampu, akan diinformasikan
POKOK BAHASAN/
kepada mahasiswa sebelum masa perkuliahan
SUBJECTS
Depend on the lecture, it will be informed to the student before semester begin
PUSTAKA UTAMA/ REFERENCES SM 092213: MULTI-KRITERIA OPTIMUM
(MATA KULIAH PILIHAN)
MATA KULIAH/
SM 092307: MULTICRITERIA OPTIMIZATION
COURSE TITLE
ITS : 2009-2014 Credits: 3 SKS / 3 Credit units
(ASSORTED COURSE TITLE)
Semester: I rriculum Cu
TUJUAN
x Mahasiswa mampu membuat model keputusan dalam
PEMBELAJARAN/
menyelesaikan masalah yang berkarakteristik multicriteria
LEARNING
secara optimal OBJECTIVES x Student able to model decision making to solve problem which
Kurikulum/ have optimal multicriteria characteristic
x Mampu mengikuti perkembangan Matematika, Sains dan Teknologi
x Able to follow development of Mathematics, science and technology
KOMPETENSI/
x Mampu mengembangkan Matematika dan Terapannya
COMPETENCY
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
POKOK BAHASAN/
x Klasifikasi masalah multikriteria
SUBJECTS
x Efisiensi dan nondominansi x Metode jumlahan terbobot x Efisiensi dan nondominansi x Metode jumlahan terbobot
PUSTAKA UTAMA/
x Matthias Ehrgott, Multicriteria Optimization, Springer Verlang Berlin, 2005
REFERENCES
x Statnikov R.B., Multicriteria Design: Optimization and Identification, Kluwer Academic Publisher, 1999
SM 092215: ANALISIS TIME SERIES
(MATA KULIAH PILIHAN)
MATA KULIAH/ SM 092215: TIME SERIES ANALYSIS COURSE TITLE
(ASSORTED COURSE TITLE)
Credits: 3 SKS / 3 Credit units ITS : 2009-2014 Semester: III
Kuliah ini mendiskusikan karakteristik dari time-series, dasar- rriculum
TUJUAN
dasar regresi, teknik untuk data time series, pemodelan Cu
PEMBELAJARAN/
univariate ARIMA, proses GARCH, dan multivariate ARMAX.
LEARNING
x The course discusses the characteristics of time series, a OBJECTIVES background in regression , techniques for time series data,
univariate ARIMA modeling, GARCH processes, and multivariate Kurikulum/ ARMAX models.
x Mampu mengikuti perkembangan Matematika, Sains dan Teknologi
x Able to follow development of Mathematics, science and technology
KOMPETENSI/
x Mampu mengembangkan Matematika dan Terapannya
COMPETENCY
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
POKOK BAHASAN/
Karakteristik dari time series
SUBJECTS
characteristics of time series
x Pengantar konsep-konsep dasar dari model plot waktu x Pengantar konsep-konsep dasar dari model plot waktu
Latar belakang dalam regresi
background in regression
teknik-teknik untuk data time-series
x techniques for time series data dan nonstatsioner x
pemodelan univariate ARIMA
univariate ARIMA modeling
x proses-proses GARCH, model threshold, regresi dengan error- eror autokorelasi, regresi tundaan, pemodelan fungsi alih
x GARCH processes, threshold models, regression with autocorrelated errors, lagged regression, transfer function modeling
Model-model multivariate ARMAX
multivariate ARMAX models.
x Kirchgässner G and J. Wolters, Introduction to Modern Time Series Analysis, Springer-Verlag, Berlin, 2007
PUSTAKA UTAMA/
x Brockwell, PJ and RA. Davis, Introduction to Time Series
REFERENCES
and Forecasting, Springer-Verlag New York, Inc McGrawHill, 2002
x Shumway RH and DS Stoffer. Time Series Analysis and Its Applications, Springer Science+Business Media, LLC,
ITS : 2009-2014
rriculum Cu
SM 092217: TEORI RESIKO DAN ANALISIS
KEPUTUSAN
Kurikulum/
(MATA KULIAH PILIHAN)
MATA KULIAH/ COURSE TITLE
SM 092217: RISK THEORY AND DECISION ANALYSIS
(ASSORTED COURSE TITLE)
Credits: 3 SKS / 3 Credit units
Semester: I
TUJUAN
x Mahasiswa mampu menerapkan matematika dalam
PEMBELAJARAN/
menganalisis resiko dalam setiap pengambilan keputusan.
LEARNING
OBJECTIVES x Student able to apply mathematics to risk analysis on decision making
KOMPETENSI/
x Mampu mengikuti perkembangan Matematika, Sains dan
COMPETENCY
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 Resiko dan analisis keputusan x Risk and decision analysis x Proses analisis keputusan x Decision analysis process x Kebijakan keputusan x Decision policy
POKOK BAHASAN/
x Utilitas dan keputusan multi kriteria
SUBJECTS
x Utility and multicriteria decision x Pohon keputusan x Decision tree x Penetapan dan bias
ITS : 2009-2014 x Judgment and bias x Menghubungkan resiko x Relating risk
rriculum x Stochastics variance
Cu
PUSTAKA UTAMA/
x Chavas J.P, Risk Analysis in Theory and Practice, Elsevier Inc,
REFERENCES
2004 x
John Schuyler , Risk and Decision Analysis in Projects, Project
Managemet Institute, Pennsylvania USA, 2001
Kurikulum/
SM 092219: SISTEM FUZZY
(MATA KULIAH PILIHAN)
MATA KULIAH/ SM 092219: FUZZY SYSTEM COURSE TITLE
(ASSORTED COURSE TITLE)
Credits: 3 SKS / 3 Credit units Semester: III
TUJUAN
x Memberikan pengetahuan tentang kenapa sistem fuzzy,
PEMBELAJARAN/
matematika sistem fuzzy, operasi pada sistem fuzzy, relasi fuzzy, variable linguistic, logika fuzzy, pengambilan 30
LEARNING
keputusan fuzzy, dan forecasting-clustering fuzzy. OBJECTIVES x To give knowledges about why fuzzy system, operation on
fuzzy system, fuzzy relationship, fuzzy logic, fuzzy decision making, and fuzzy clustering/forecasting.
x Mampu mengikuti perkembangan Matematika, Sains dan Teknologi
x Able to follow development of Mathematics, science and technology
KOMPETENSI/
x Mampu mengembangkan Matematika dan Terapannya
COMPETENCY
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 Kenapa sistem fuzzy? x Why fuzzy system? x Matematika Himpunan Crsip vs Fuzzy x Mathematics Crisp vs Fuzzy Set x Fungsi keanggotaan x Membership function
ITS : 2009-2014
POKOK BAHASAN/
x Operasi-operasi pada himpunan fuzzy
SUBJECTS
x Operation on Fuzzy Set x Variabellinguistic
rriculum x Linguistic Variables
Cu x Relasi fuzzy, dan Logika Fuzzy
x Fuzzy relation and fuzzy logic x Model-model pengambilan keputusan fuzzy x Models of fuzzy decision making x Forecasting dan clustering fuzzy
Kurikulum/ x Fuzzy forcasting and clustering
x Buckley J, and E. Eslami, An Introduction to Fuzzy Logic and Fuzzy Sets , Physica Heidelberg, 2001,
PUSTAKA UTAMA/
x Klir, GJ and B. Juan, Fuzzy Set and Fuzzy Logic, Prentice Hall, New Jersey, 2001
REFERENCES
x Zimmerman H.J, Fuzzy Set Theory and Its Applications, Kluwer Academic Publisher, 1996.
x Zadeh, LA., Fuzzy Sets, Fuzzy Logic, and Fuzzy Systems: Selected Papers , Kluwer Academic Publisher, 1996
SM 092221: PENGOLAHAN CITRA
(MATA KULIAH PILIHAN)
MATA KULIAH/ SM 092221: IMAGE PROCESSING COURSE TITLE
(ASSORTED COURSE TITLE)
Credits: 3 SKS / 3 Credit units
Semester: I
TUJUAN
x Mahasiswa mampu memahami konsep dasar dari pengolangan
PEMBELAJARAN/
citra digital dan menerapkannya ke aplikasi yang lebih kompleks
LEARNING
x Students are able to comprehend basic concepts of digital OBJECTIVES image processing and apply it to more complex application.
x Mampu mengikuti perkembangan Matematika, Sains dan Teknologi
x Able to follow development of Mathematics, science and ITS : 2009-2014 technology
KOMPETENSI/
x Mampu mengembangkan Matematika dan Terapannya
COMPETENCY
x Able to develop Mathematics and its applications
rriculum x Mampu mengimplementasikan kerangka berfikir matematis