Department of Informatics and Computer Engineering

Inspire technology through innovation and excellence with Information Technology and Computer Engineering

At this time the need for information technology plays a very important role and in the future it will become the backbone of the nation's economic growth.

Therefore, the Electronic Engineering Polytechnic Institute of Surabaya established the Department of Informatics and Computer Engineering which consists of five study programs, namely D3 Informatics Engineering, D4 Informatics Engineering, D4 Computer Engineering, D4 Applied Data Science, and S2 Applied Informatics and Computer Engineering.

Department of Information and Computer Technology aims to become a center of excellence for engineering technology education in the field of emerging technology related fields of Information Technology and Computers to produce graduates who are ready to compete in the global market.

The Department of Informatics and Computer Engineering has produced many highly qualified graduates who work as Programmer, Software Engineer, Hardware Designer, Network Administrator, Computer System Analyst, Information Technology Engineer, Manager/Supervisor, Services/Technical Support, Marketing/Sales, and others.

FIELDS of STUDY

TECHNICAL INFORMATION

COMPUTER ENGINEERING

APPLIED DATA SCIENCE

TECHNICAL INFORMATION

Laboratory

Information Systems Laboratory

The Information Systems Laboratory supports teaching activities for courses in Information Technology Concepts, Basic Computer Systems, Web Design, Web Programming, Framework Programming, Mobile Device Programming, and Web-Based Applications. The Information Systems Laboratory also conducts research in the fields of e-government information systems, Massive Open Online Course (MOOC), and adaptive learning.

 Database Laboratory 

The Database Laboratory supports teaching activities for Database, Advanced Database, Database Administration, and Data Warehouse courses. The Database Laboratory also conducts research in the fields of big data engineering and data warehouse.

Software Engineering Laboratory

The Software Engineering Laboratory supports teaching activities for courses in Software Engineering, User Experience Design, Network Administration and Management, Software Modeling, Software Development, and Software Management. The Software Engineering Laboratory also conducts research in the fields of UI/UX Design, Software Development Models, and Agile Software Development.

 Soft Computation Laboratory

The Soft Computation Laboratory supports teaching activities for courses in Programming Concepts, Logic and Algorithms, Algorithms and Data Structures, Object Oriented Programming, Computational Intelligence, Decision Support Systems, Advanced Programming, Machine Learning, and Data Mining. The Soft Computation Laboratory also conducts research in the fields of knowledge engineering, machine learning, and data mining.

Computer Vision Laboratory

The Computer Vision Laboratory supports teaching activities for courses in Image Processing, Geographic Information Systems, and Computer Vision. The Computer Vision Laboratory also conducts research in the fields of Computational Video, Image Segmentation/Classification, biomedical analysis, and Geographic Information Systems.

Computer Network Laboratory

The Computer Network Laboratory supports teaching activities for courses in Operating Systems, Network Concepts, Network Security, Computing and Cloud Applications. The Computer Network Laboratory also conducts research in the fields of distributed networks, intrusion detection systems, DevSecOps, network management systems, and the Internet of things.

COURSES

Software Engineer Course

The Software Engineer Course consists of courses in Software Engineering, User Experience Design, Software Modeling Workshop, Advanced Programming Workshop, Software Development, and Software Development Practicum.

Learning Characteristics

The Software Engineer Course aims to achieve learning so that students are able to develop software to produce quality software on various platforms through needs analysis, design stages, implementation, testing, and maintenance by applying scientific and mathematical principles in accordance with code writing standards and technical design. which is based on Agile development principles.

System Analyst Course

The System Analyst Course consists of Computational Intelligence, Computational Intelligence Practicum, Statistics and Probability, Decision Making Systems, and Machine Learning Workshops.

Learning Characteristics

The System Analyst Course aims to achieve learning so that students are able to use information technology systems in an organization to achieve business goals, are able to understand a system and perform system analysis, are able to design and develop new systems, are able to implement and be responsible in discussing with management and users to determine system requirements, identify inputs and outputs that will meet user requirements as the system is developed, able to use the principles of structured analysis, to ensure that the solutions offered are effective, cost-effective and financially feasible, able to create diagrams, flow charts, and specifications that will used by software engineers and IT engineers, and capable of managing applications, coordinating tests, and monitoring system performance to ensure improvements.

Information Technology Engineer Course

The Information Technology Engineer Course consists of courses in Framework Programming Workshop, Network Concepts, Network Concept Practicum, Mobile Device Programming Workshop, Network Administration and Management Workshop, Network Security Workshop, Database Administration Workshop, and Data Warehouse Workshop.

Learning Characteristics

The Information Technology Engineer Course aims to achieve learning so that students have expertise in designing, installing and maintaining computer systems, database system technology, computing technology, system infrastructure and have the ability to test, configure and troubleshoot hardware, software and network system problems. to meet user needs.

COMPUTER ENGINEERING

Laboratory

Computer Vision & Graphics Laboratory

The Computer Vision & Graphics Laboratory supports teaching activities for courses in Signals and Systems, Robotics, Computer Vision, Real Time Operating Systems, Mobile and Distrubuted Computing. The Computer Vision & Graphics Laboratory also conducts research in the field of robotics, facial recognition, computational video.

Real Time Programming Laboratory

Real Time Programming Laboratory supports teaching activities for courses in Computer Algorithms and Programming, Software Design, Product Engineering Workshops. The Real Time Programming Laboratory also conducts research in the field of Timing Analysis and Scheduling Algorithms.

Real Time Computer System Laboratory

The Real Time Computer System Laboratory supports teaching activities for the Database, Sensor and Actuator Workshops, Logic Circuits, Computer Architecture and Organization, Embedded Systems, Embedded Workshop courses. Real Time Computer Systems Laboratory also conducts research in the field of real time operating systems, Kernels for Embedded Systems, Advanced Embedded Systems.

Analog Systems Laboratory

The Analog Systems Laboratory supports teaching activities for Electrical Circuit courses, Analog Systems Workshops, Instrumentation and Telemetry Workshops. The Analog Systems Laboratory also conducts research in the field of Analog Signal Processing.

Digital Laboratory

The Digital Laboratory supports teaching activities for Electronic Circuit, Communication System and Networking courses, Workshop on Digital Systems, Network and Information Security. Digital Laboratory also conducts research in the field of Digital Signal Processing.

COURSES

Embedded system and Operating System Course

The Embedded system and Operating System Course consists of courses in Computer Algorithms and Programming, Software Design, Product Engineering Workshops, Database Workshops, Sensors and Actuators, Logic Circuits, Computer Architecture and Organization, Embedded Systems, Embedded Workshops.

Learning Characteristics

The Embedded system and Operating System Course aims to achieve learning so that students are able to design, implement and innovate in the field of embedded systems and real-time operating systems: Understanding the basic concepts of embedded systems and their applications. Able to design solutions based on embedded systems to solve various kinds of problems. Mastering the basic concepts of human-machine interaction. Apply the concept of human and machine interaction in embedded systems. Understand the concept of pervasiveness and sensors in embedded system applications.

Networking Course

The Networking Course consists of Electrical Circuits, Analog Systems Workshops, Instrumentation and Telemetry Workshops, Electronic Circuits, Communication Systems and Networking, Digital Systems Workshops, Network and Information Security.

Learning Characteristics

The Networking Course aims to achieve learning so that students are able to design network devices, implementation, network management and security in network systems. Able to explain the concept of computer networks based on OSI Layer Able to perform troubleshooting of connectivity problems on computer networks. Able to improve network performance by implementing a high availability system. Able to design network architecture for very high traffic. Understand the concept of information security and security on computer networks. Able to apply reliable data security methods according to the problems encountered. Recognizing various kinds of threats in the cyber world and taking mitigation actions to protect information security.

Robotics and Smart System Course

The Robotics and Smart System Course consists of courses in Signals and Systems, Robotics, Computer Vision, Real Time Operating Systems, Mobile and Distrubuted Computing.

Learning Characteristics

The Robotics and Smart System Course aims to achieve learning so that students are able to design, implement and innovate in the field of robotics technology and intelligent systems. Can operate 2 and 3 dof arm robot. Can make trajectory planning. Understand and apply DH-Parameters. Controlling mobile robots.

APPLIED DATA SCIENCE

Laboratory

Data Analysis Laboratory

The Data Analyst Laboratory supports teaching activities for Basic Statistics, Programming, Logic and Algorithms, Statistical and Probability Modeling, Advanced Statistics, Applied Data Analytics, and Social Media Analysis. The Data Analyst Laboratory also conducts research in the fields of data analysis of e-government, industry, and social media.

 Data Processing Laboratory

The Data Processing Laboratory supports teaching activities for courses in Databases, Text Processing, Data Management, Text Mining, Data Exploration and Visualization, Descriptive Mining, Neuro Computing, Knowledge Modeling, and Recommendation Systems. The Data Processing Laboratory also conducts research in the fields of e-government, industrial, and social media data processing.

Data Engineering Laboratory

The Data Engineering Laboratory supports teaching activities for courses in Artificial Intelligence, Machine Learning, Web Technology & Services, Application Development, Big Data Infrastructure & Management, Big Data Technology & Tools, Cloud Computing, and Mobile Application Development. The Data Engineering Laboratory also conducts research in e-government, industrial, and social media data engineering.

COURSES

Data Scientist Course

The Data Scientist Course consists of courses in Database, Text Processing, Data Management, Text Mining, Data Exploration and Visualization, Descriptive Mining, Neuro Computing, Knowledge Modeling, and Recommendation Systems.

Learning Characteristics

The Data Scientist Course aims to achieve learning so that students are able to analyze and interpret very large amounts of data, both structured and unstructured, to describe data, map data similarity and develop hypotheses and models, with a multidisciplinary blend of data inference, algorithm development and technology from computer science , artificial intelligence and statistics, to solve analytically complex problems, present the patterns in the form of visualizations and generate business intelligence solutions.

Data Analyst Course

The Data Analyst Course consists of courses in Basic Statistics, Programming, Logic and Algorithms, Statistical and Probability Modeling, Advanced Statistics, Applied Data Analytics, and Social Media Analysis.

Learning Characteristics

The Data Analyst Course aims to achieve learning so that students are able to collect data from various data sources, organize data effectively to understand data patterns and relationships, transform data into effective forms for analyzing and interpreting data, management and analysis of data from various data sources, seeing relationships data in data collections and analyze trends, with computer science, statistics and mathematics approaches, and visualize the results of data analysis, to reveal hidden knowledge, and patterns of data, which is an added value for the industry/company.

Data Engineer Course

The Data Engineer Course consists of courses in Artificial Intelligence, Machine Learning, Web Technology & Services, Application Development, Big Data Infrastructure & Management, Big Data Technology & Tools, Cloud Computing, and Mobile Application Development.

Learning Characteristics

The Data Engineer Course aims to achieve learning so that students are able to develop, build, test and maintain architectures for databases and large-scale processing systems, set up big data infrastructure, integrate data in infrastructure, manage workflows, pipelines, and ETL processes, convert data into formats that are useful for analysis, and managing infrastructure to ensure it is easily accessible and functions smoothly, and optimizes the performance of the big data ecosystem..

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