2011 Curriculum Design Program Pasca Sarjana Magister Teknik Informatika Universitas Dian Nuswantoro

SD Sompok Semarang (1987) SMPN 8 Semarang (1990) SMA Taruna Nusantara, Magelang (1993) S1, S2 dan S3 (on-leave) Department of Computer Sciences Saitama University, Japan ( ) Research Interests: Software Engineering, Intelligent Systems LIPI Researcher ( ) Founder dan Koordinator IlmuKomputer.Com CEO PT Brainmatics Cipta Informatika Contacts: – Blog: romisatriawahono.net – FB: facebook.com/romisw Phone: Romi Satria Wahono

Curriculum Foundation

Curriculum A curriculum is the set of courses, and their content, offered at a university or school A curriculum is prescriptive, and is based on a more general syllabus which merely specifies: 1.what topics must be understood 2.what level to achieve a particular grade or standard

Curriculum Foundation 1.Computing Curricula 2005: The Overview Report, ACM and IEEE CS, Computer Science Curriculum 2008, ACM and IEEE CS, Curriculum Guidelines for Graduate Degree Programs in Software Engineering, Integrated Software & Systems Engineering Curriculum Project, Model Curriculum and Guidelines for Graduate Degree Programs in Information Systems, Communications of Association for Information Systems (AIS), Curriculum Guidelines for Undergraduate Degree Programs in Information Systems, ACM and AIS, Curriculum Guidelines for Undergraduate Degree Programs in Information Technology, ACM and IEEE CS, 2008

IEEE/ACM Computing Curricula 2005 Computer Engineering (CE) pengembangan sistem terintegrasi (software dan hardware) Computer Engineer Information System (IS) analisa kebutuhan dan proses bisnis serta desain sistem System Analyst Information Technology (IT) pengembangan dan pengelolaan infrastruktur IT Network Engineer Computer Science (CS) konsep computing dan pengembangan software Computer Scientist Software Engineering (SE) pengembangan software dan pengelolaan tahapan SDLC Software Engineer

Information Systems vs Computer Science Information Systems (IS): IS, IT aspek manusia, organisasi, manajemen dan pemanfaatan metode computing Computer Science (CS): CS, CE, SE aspek teknis dari metode computing

Curriculum Design

Mengikuti standard IEEE/ACM Computing Curricula 2005, baik secara naming maupun content Mata kuliah (Course) secara umum terbagi 4 bagian: 1.Foundation Course (0 SKS) 2.Fundamental Course (11 SKS) 3.Core Course (16 SKS) 4.Concentration Course (15 SKS) Model kurikulum adalah paket, yang berarti bahwa mahasiswa wajib menyelesaikan total 48 SKS yang terbagi dalam 20 mata kuliah dan melakukan penelitian tesis dengan supervisi dosen pembimbing Mata kuliah dan penelitian tesis didesain untuk bisa diselesaikan oleh mahasiswa dalam waktu 18 bulan (3 semester)

Curriculum Design ISITCSSE Fundamental Courses (11) Core Courses (16) Business Intelligence (15) Intelligent Systems (15) Thesis (6) Foundation Courses (0)

Academic Calendar Semester 0 Semester 1 Semester 2 Semester 3 Triwulan 1 Triwulan 2 Triwulan 1 Triwulan 2 Triwulan 1 Triwulan 2 FOUNDATION COURSES (0) FUNDAMENTAL COURSES (11) CORE COURSES (16) CONCENTRATION COURSES (15) Foundation of Information Systems Information Retrieval Systems Analysis and Design Research Methodology Machine Learning Multimedia and Game Design Automated Software Engineering Foundation of Database Systems Formal Methods Decision Support Systems Image Processing Soft Computing Computer Vision Foundation of Technopreneu rship Artificial Intelligence Software Engineering e-Business IT Audit and Controls IT Governance Foundation of Intelligent Systems Algorithms and Complexity Data Mining Business Intelligence Enterprise Architecture Foundation of Algorithms and Data Structure Thesis

Concentration Design Business Intelligence (IS, IT) Intelligent Systems (CE, CS, SE)

Course-Competency Mapping Business Intelligence Foundation of Information Systems Foundation of Database Systems Foundation of Technopreneurship Information Retrieval Decision Support Systems Systems Analysis and Design Data Mining e-Business IT Audit and Controls IT Governance Business Intelligence Enterprise Architecture Intelligent Systems Foundation of Intelligent Systems Foundation of Algorithms and Data Structure Formal Methods Artificial Intelligence Algorithms and Complexity Software Engineering Image Processing Machine Learning Soft Computing Computer Vision Multimedia and Game Design Automated Software Engineering

Business Intelligence vs Intelligent Systems

Foundation Courses (0) Main Objectives: – Mengenalkan bidang ilmu computing yang diajarkan di program pasca sarjana secara umum – Memberikan rangkuman, refresh dan matrikulasi sehingga mahasiswa siap mengikuti pembelajaran di level S2 Schedule: – Semester 0 (Pra Semester) Total Credits: – 0 SKS

Foundation Courses (0) 1.Foundation of Information Systems 2.Foundation of Database Systems 3.Foundation of Technopreneurship 4.Foundation of Intelligent Systems 5.Foundation of Algorithms and Data Structure

Fundamental Courses (11) Main Objectives: – Memahamkan bidang ilmu dasar computing, yang menjadi bekal wajib bagi mahasiswa untuk bisa mengikuti Core Courses – Memperkuat skill pemrograman sehingga mempermudah mahasiswa menguasai implementasi berbagai metode computing yang ada di seluruh materi – Merekomendasikan Java, yang merupakan standard defacto bahasa pemrograman di dunia akademisi (sebagian besar textbook computing menggunakan Java) Schedule: – Semester 1 Triwulan 1 Total Credits: – 11 SKS

Fundamental Courses (11) 1.Information Retrieval (3) 2.Formal Methods (2) 3.Artificial Intelligence (3) 4.Algorithms and Complexity (3)

Information Retrieval Definition: – The area of study concerned with finding material (documents) of an unstructured nature (text) that satisfies an information need from within large collections (flat file, database or web) Textbook: – Christopher D. Manning, Prabhakar Raghavan, Hinrich Schütze, Introduction to Information Retrieval, Cambridge University Press, 2008 – Bruce Croft, Donald Metzler, Trevor Strohman, Search Engines: Information Retrieval in Practice, Addison Wesley, 2009

Information Retrieval Systems

Formal Methods Definition: – The application of theoretical computer science fundamentals, in particular discrete mathematics, logic calculi, formal languages, automata theory, and program semantics, but also type systems and algebraic data types to problems in software engineering Textbook: – James A. Anderson, Automata Theory with Modern Applications, Cambridge University Press, 2006 – Jean-Francois Monin and M.G. Hinchey, Understanding Formal Methods, Springer, 2003

Mathematical Logic

Finite Automata for Game Design

Artificial Intelligence Definition: – The study and design of intelligent machines and agents that can engage on behaviors that humans consider intelligent – Inteligent agents is a system that perceives its environment and takes actions that maximize its chances of success Textbook: – Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (Third Edition), Pearson Education, 2010 – David L. Poole and Alan K. Mackworth, Artificial Intelligence: Foundations of Computational Agents, Cambridge University Press, 2010

AI Applications

Algorithms and Complexity Definition: – The study and design of algorithm, a method for solving problems on computer programming, and the analysis of its complexity, a cost measured in running time, or storage, or whatever units are relevant Textbook: – Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein, Introduction to Algorithms (Third Edition), The MIT Press, 2009 – Cay Horstmann, Big Java (Fourth Edition), John Wiley & Sons, 2010

Java Programming

Algorithms

Computational Complexity

Core Courses (16) Main Objectives: – Menajamkan pemahaman dan penguasaan inti ilmu computing dengan lebih dalam dan komprehensif – Core Courses merupakan inti dari materi pada program pasca sarjana udinus Schedule: – Semester 1 Triwulan 2  Semester 2 Triwulan 1 Total Credits: – 16 SKS

Core Courses (16) 1.Decision Support Systems (3) 2.Data Mining (3) 3.Systems Analysis and Design (2) 4.Image Processing (3) 5.Software Engineering (2) 6.Research Methodology (3)

Decision Support Systems Definition: – a computer-based information system that supports business or organizational decision-making activities and serve the management, operations, and planning levels of an organization and help to make decisions, which may be rapidly changing and not easily specified in advance Textbook: – Efraim Turban, Ramesh Sharda, Dursun Delen, Decision Support and Business Intelligence Systems (9th Edition), Prentice Hall, 2010 – Carlo Vercellis, Business Intelligence: Data Mining and Optimization for Decision Making, John Wiley & Sons, 2009

Data Mining Definition: – The area of study concerned with extracting implicit, previously unknown, potentially useful information from data and discovering meaningful new correlations, patterns and trends by sifting through large amounts of data stored in repositories, using pattern recognition and machine learning technologies as well as statistical and mathematical techniques Textbook: – Ian H. Witten, Frank Eibe, Mark A. Hall, Data mining: Practical Machine Learning Tools and Techniques (3rd Edition), Elsevier, 2011 – Daniel T. Larose, Discovering Knowledge in Data: an Introduction to Data Mining, John Wiley & Sons, 2005

Data Mining Process

Algoritma C4.5 untuk Prediksi Calon Legislatif

Algoritma C4.5 untuk Prediksi Kelulusan Mahasiswa

Systems Analysis and Design Definition: – The process of analyzing, defining and modeling the business process, architecture, components, modules, interfaces, and data for a software system to satisfy specified requirements – Unified Modeling Language (UML) is a standard language for representing the process Textbook: – Alan Dennis, Barbara Haley Wixom, David Tegarden, Systems Analysis and Design with UML (3rd Edition), John Wiley and Sons, 2010 – Gary B. Shelly, Thomas J. Cashman, Harry J. Rosenblatt, Systems Analysis and Design (9th Edition), Course Technology, 2010

Sistem ATM

UML

Image Processing Definition: – The area of study concerned with any form of signal processing for which the input is an image, such as a photograph or video frame, and the output are either an image or a set of characteristics or parameters related to the image – Most image-processing techniques involve treating the image as a two-dimensional signal and applying standard signal processing techniques to it Textbook: – Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing (3rd edition), Prentice Hall, 2007 – Wilhelm Burger and Mark J. Burge, Digital Image Processing: An Algorithmic Introduction using Java, Springer, 2007

Face Recognition

Image Watermarking

Software Engineering Definition: – The field and study on systematic approach to the analysis, design, constructing, testing, maintenance and reengineering of software, so that it is of high quality, affordable, maintainable, and fast to build Textbook: – Roger S. Pressman, Software Engineering: A Practitioner’s Approach (7th Edition), McGraw-Hill, 2009 – Ian Sommerville, Software Engineering (9th Edition), Addison-Wesley, 2010

Research Methodology Definition: – A collective term for the structured processes and methods of conducting research – Research is the search for knowledge, or as any systematic investigation, to establish novel facts, solve new or existing problems, prove new ideas, or develop new theories, usually using a scientific method Textbook: – Christian W. Dawson, Project in Computing and Information System a Student Guide (2nd Edition), Addison-Wesley, 2009 – Mikael Berndtsson, Jörgen Hansson, Björn Olsson, Björn Lundell, Thesis Projects - A Guide for Students in Computer Science and Information System (2nd Edition), Springer-Verlag London Limited, 2008

Concentration Design (15) Business Intelligence (IS, IT) Intelligent Systems (CE, CS, SE)

Concentration Design (15) 1.Business Intelligence (BI) – Materi dan penelitian mengarah ke aspek manusia, organisasi dan manajemen, misalnya analisa pemanfaatan metode/sistem computing dan information technology untuk keperluan (manajemen) organisasi – Teori dan model yang digunakan untuk penelitian biasanya menggunakan information systems theories – Metode penelitian menggunakan kuantitatif (eksperimen, deskriptif kuantitatif) atau kualitatif (case study) – Tepat untuk mahasiswa yang kuat di bidang matematika statistik dan manajemen, dengan profesi manajerial dan pembuat kebijakan pada organisasi, seperti manajer, kepala divisi, auditor, project manager, kepala sekolah, ketua stmik, ketua yayasan, dsb 2.Intelligent Systems (IS) – Materi dan penelitian mengarah aspek teknis dari metode computing, misalnya berupa pengujian, pengembangan dan penemuan teori/model/metode computing – Metode penelitian menggunakan kuantitatif (eksperimen) – Teori dan model yang digunakan untuk penelitian biasanya menggunakan computing theories – Tepat untuk mahasiswa yang kuat di bidang matematika komputasi, fresh graduate, dengan profesi lebih ke arah technical, seperti dosen, developer, peneliti, network engineer, dsb

Business Intelligence vs Intelligent Systems

Concentration Courses (15): Business Intelligence Main Objectives: – Mengenalkan research trends dan state-of the-art dari berbagai bidang di Information Systems – Memahamkan berbagai contoh penelitian pada bidang Information Systems sehingga mempermudah mahasiswa konsentrasi Business Intelligence dalam penentuan topik penelitian untuk penyusunan tesis Schedule: – Semester 2 Triwulan 2  Semester 3 Total Credits: – 15 SKS

Concentration Courses (15): Business Intelligence 1.e-Business (3) 2.IT Audit and Controls (3) 3.IT Governance (3) 4.Business Intelligence (3) 5.Enterprise Architecture (3)

Concentration Courses (15): Intelligent Systems Main Objectives: – Mengenalkan research trends dan state-of the art dari berbagai bidang di Intelligent Systems – Memahamkan berbagai contoh penelitian pada bidang Intelligent Systems sehingga mempermudah mahasiswa konsentrasi Intelligent Systems dalam penentuan topik penelitian untuk penyusunan tesis Schedule: – Semester 2 Triwulan 2  Semester 3 Total Credits: – 16 SKS

Concentration Courses (15): Intelligent Systems 1.Machine Learning (3) 2.Soft Computing (3) 3.Computer Vision (3) 4.Multimedia and Game Design (3) 5.Automated Software Engineering (3)

Concentration Design (Alternative) Business Intelligence Intelligent Systems Game Technology Software Engineering

Concentration Courses: Game Technology 1.Game Programming 2.Advanced Game Programming 3.Graphics Design and 3D Modeling 4.Game Design and Development 5.Scenario and Immersive Environment

Concentration Courses: Software Engineering 1.Software Requirements 2.Object Oriented Analysis and Design 3.Human-Computer Interaction 4.Software Construction 5.Software Testing and Quality Assurance

Academic Calendar Semester 0 Semester 1 Semester 2 Semester 3 Triwulan 1 Triwulan 2 Triwulan 1 Triwulan 2 Triwulan 1 Triwulan 2 FOUNDATION COURSES (0) FUNDAMENTAL COURSES (11) CORE COURSES (16) CONCENTRATION COURSES (15) Foundation of Information Systems Information Retrieval Systems Analysis and Design Research Methodology Machine Learning Multimedia and Game Design Automated Software Engineering Foundation of Database Systems Formal Methods Decision Support Systems Image Processing Soft Computing Computer Vision Foundation of Technopreneu rship Artificial Intelligence Software Engineering e-Business IT Audit and Controls IT Governance Foundation of Intelligent Systems Algorithms and Complexity Data Mining Business Intelligence Enterprise Architecture Foundation of Algorithms and Data Structure Thesis

Standard Course Features 1.Satuan Acara Perkuliahan (SAP) 2.Textbook: 1.Referensi Utama (pdf) 2.Referensi Pendamping (pdf) 3.Slide Presentasi (ppt)

Student Research

Research Procedure 1.Semester 2 triwulan 1, mahasiswa memilih konsentrasi 2.Semester 2 triwulan 2, mahasiswa sudah harus bergabung ke konsentrasi dan mengikuti seluruh prosedur bimbingan oleh dosen pembimbing 3.Setiap konsentrasi dipimpin oleh seorang kepala konsentrasi yang bertanggung jawab terhadap penelitian mahasiswa pada konsentrasi yang dipimpin

Research Group 1.Business Intelligence: 1.IT Governance 2.Business Intelligence 2.Intelligent Systems: 1.Computer Vision 2.Soft-Computing and Machine Learning

Research Features 1.Disediakan ruangan khusus untuk setiap konsentrasi 1.Intelligent Systems Research Group 2.Business Intelligence Research Group 2.Mahasiswa dapat melakukan penelitian, berdiskusi dengan rekan atau pembimbingnya untuk menyelesaikan penelitian tesis di ruangan khusus konsentrasi 3.Diskusi dan pembimbingan juga dapat dilakukan dengan menggunakan pertemuan pada mata kuliah konsentrasi

Research Plan

Sidang Wajib Prasyarat Kelulusan 1.Sidang Proposal 2.Kolokium (Terbuka) 3.Sidang Akhir

Research Plan (Graduation: April) September-Oktober: – Penetapan masalah dan approach (metode/model) yang digunakan – Objectifikasi masalah (field study and literature study) – Memahami approach (metode/model) yang akan digunakan (baca buku, coba satu studi kasus) Oktober -Desember: – Menguasai tool yang akan digunakan untuk implementasi approach (metode/model) – Memahami state-of-the-art dari approach yang dipilih (baca journal) – Menyusun proposal penelitian dan submission ke administrasi kampus – Menyelesaikan Bab I dan Bab II (diambil dari proposal penelitian) Desember-Pebruari: – Selesaikan Bab III (sampai eksperimen awal penelitian)  siap ujian Proposal – Perbaiki eksperimen sehingga mendapatkan hasil maksimal Pebruari-Maret: – Penerapan dan Pengukuran Penelitian – SelesaikanTesis – Ujian Kolokium – Ujian Tesis

Research Plan (Graduation: Oktober) Maret-April: – Penetapan masalah dan approach (metode/model) yang digunakan – Objectifikasi masalah (field study and literature study) – Memahami approach (metode/model) yang akan digunakan (baca buku, coba satu studi kasus) April -Mei: – Menguasai tool yang akan digunakan untuk implementasi approach/metode – Memahami state-of-the-art dari approach yang dipilih (baca journal) – Menyusun proposal penelitian dan submission ke administrasi kampus – Menyelesaikan Bab I dan Bab II (diambil dari proposal penelitian) Mei-Agustus: – Selesaikan Bab III (sampai eksperimen awal penelitian)  siap ujian Proposal – Perbaiki eksperimen sehingga mendapatkan hasil maksimal Agustus-September: – Penerapan dan Pengukuran Penelitian – SelesaikanTesis – Ujian Kolokium – Ujian Tesis

Concentration: Business Intelligence (BI)

Enterprise Architecture Business Intelligence Related Computing Disciplines IT Governance Information Systems Decision Support Systems IT Audit and Controls

Types of Information Systems

Theories Used in IS Research

Main Journal Publications 1.Management Information Systems Quarterly (MISQ) 2.Information Systems Research (ISR) 3.Journal of Association of Information Systems (JAIS) 4.Journal of Management Information Systems (JMIS) 5.European Journal of Information Systems (EJIS), and Information Systems Journal (ISJ) 6.ACM Transaction on Management Information systems 7.ACM Transaction on Information Systems

Concentration: Intelligent Systems (IS)

Forum Diskusi 1.FB Group: Intelligent Systems Research Center Intelligent Systems Research Center 2.Milis:

Intelligent Systems The software systems that perceive, reason, learn, and act intelligently (IEEE Intelligent Systems) A software system that has a main objective, and chooses an action based on its experiences and rules. It can learn by generalizing the experiences it has stored in its memories (intelligent-systems.com) Any formal or informal system to manage data gathering, to obtain and process the data, to interpret the data, and to provide reasoned judgments to decision makers as a basis for action (US Department of Defense, 2005)

Research Interest The central theme of the Intelligent Systems Research Center is the solution to complex, distributed tasks using computer systems These include computer based diagnosis, pattern recognition and classification, software agent, information retrieval, data mining and game technology We apply our research to the industries, enterprises, hospitals, and education organization

Information Retrieval Soft-Computing Related Computing Disciplines Game Technology Software Engineering Data Mining Computer Vision

Research Themes Soft-Computing: – Fuzzy Inference Systems – Case-based Reasoning Computer Vision: – Image and Voice Recognition – Augmented Reality Data Mining and Information Retrieval: – Clustering, Classification and Association Rules Algorithm – Information Retrieval Models and Techniques – Latent Semantic Analysis Software Engineering: – Automated Software Testing – Software Quality Prediction – Software Process Improvement Game Technology: – Algorithm Game Engine – Simulation/Education/God Game Development – Adaptive Behavior on Game

Main Journal Publications ACM Transactions IEEE Transactions