The Philosophy of Informatics course at the master degree of the Informatics Study Program discusses philosophical concepts relevant to the development and application of informatics technology, including computational ethics, epistemology, technological ontology, and the social and cultural impacts of information technology. Through critical studies, students are invited to understand the relationship between philosophical theory and informatics science and integrate philosophical principles in designing technological solutions that are responsible, sustainable, and beneficial to society.

The Research Methodology course at the master degree of Informatics study program provides an in-depth understanding of relevant research methods in the field of Informatics. This course discusses research steps, data collection and analysis techniques, and the application of appropriate research methods to produce quality scientific research. The scope includes the formulation of research problems, selection of research methods, data collection techniques, data analysis, and preparation of research reports that meet scientific standards. By taking this course, students are expected to be able to design and carry out quality research and prepare research reports that can be published scientifically.

The Field Study course at the master degree of the Informatics study program aims to provide practical experience to students in applying the knowledge and skills that have been learned in the classroom to real situations in the field. Students will be involved in field projects relevant to the field of Informatics, such as software development, data analysis, information security, or other topics in accordance with industry needs. The scope of this course includes an in-depth understanding of the challenges and solutions faced in field projects, as well as the development of the ability to collaborate, communicate, and solve problems effectively in teams. Through this course, students are expected to develop practical skills that can improve their readiness to face the world of work in the Informatics industry.

The Statistics and Probability course at the master degree of the Informatics Study Program provides an in-depth understanding of the basic concepts of statistics and probability and their application in the field of informatics. This course discusses probability distribution, parameter estimation, hypothesis testing, regression analysis, and various other statistical methods relevant for data analysis and decision making. Students will be invited to integrate statistical and probability methods in research and the development of data-based information systems to support accurate and scientifically based decision making in the field of informatics.

The Artificial Intelligence course at the master degree of the Informatics study program discusses the concepts, techniques, and applications of artificial intelligence. The purpose of this course is to provide an in-depth understanding of various methods and algorithms in the development of artificial intelligence systems and be able to implement them in various fields such as natural language processing, computer vision, and machine learning. The scope includes knowledge modeling, fuzzy logic, artificial neural networks, genetic algorithms, and expert systems.

This course studies the concepts and best practices of distributed systems in computing purposes with computer network services. This course discusses an overview of the OSI and TCP/IP computer network layers at the Network, Transport, and Application levels, as well as their application to computational load sharing using basic Socket and Message Queue communication. The use of these technologies is aimed at solving actual problems in a scalable and near real-time manner.

The Software Technology course at the master degree of the Informatics study program discusses the latest concepts, principles and techniques in software development. This course aims to deepen the understanding of software development methodologies, the latest technology in software development, and best practices in software project management. The scope of the course includes software modeling, requirements analysis, software architecture design, software testing, and software configuration management.

The Data Mining course at the master degree of the Informatics study program aims to equip students with the ability to extract patterns or useful information from big data using data mining techniques and methods. Students will learn the basic concepts, techniques, and tools used in the data mining process and be able to apply them to various fields. The scope of this course includes data processing, statistical analysis, machine learning, and the use of specialized software for data mining. In addition, this course is designed to support students' readiness to face the Data Warehouse Director scheme competency test, which includes competency units such as determining business objectives, making project plans, conducting reviews, compiling business architecture roadmaps, and making final reports on data mining projects.

The Network Security and Cryptography course at the master degree of the Informatics study program aims to provide an in-depth and integrated understanding of the concepts, techniques, and implementation of network security and cryptography. Students will learn computer network protection techniques, risk analysis, security protocols, and implementation of encryption and decryption to protect information in computer systems. In addition, this course also includes a discussion of the development of security strategies based on the latest technology and the application of cryptography in various industrial and research contexts. By combining theory and practice, this course supports the development of students' analytical and innovative abilities in solving security challenges in the era of digital transformation.

The Game, Augmented, and Virtual Reality Development course at the master degree of the Informatics Study Program aims to provide a comprehensive understanding of the latest concepts, techniques, and practices in the development of game-based applications, augmented reality (AR), and virtual reality (VR). Students will learn various aspects of technology in the gaming and virtual reality industry, including game programming, user interaction design, 3D content development, AR integration, and VR implementation. This course emphasizes students' ability to design and develop innovative applications based on games, AR, and VR that meet global industry standards. The scope of the course includes theory, simulation, to the development of applicable and research-based application projects. Students are expected to be able to produce high-quality projects that support technological development and have the potential to become creative solutions in various fields.

The Feature Engineering and Machine Learning course at the Master of Informatics study program aims to provide a comprehensive understanding of feature engineering techniques and the application of machine learning in the development of data-based solutions. This course covers the mastery of basic concepts of feature engineering, feature analysis, and the use of machine learning algorithms for pattern recognition, classification, and data prediction. The scope includes modeling, extraction, selection, and evaluation of features, as well as the application of machine learning methods in solving complex problems in various fields of Informatics. Students are expected to be able to integrate feature engineering techniques with machine learning algorithms to produce innovative and effective solutions, which support the development of the latest technology in accordance with the needs of industry and society.

Digital Image Processing and Analysis courses at the Master of Informatics Study Program level provide an in-depth understanding of the concepts, techniques, and applications of digital image processing for various needs. Students will learn 2D and 3D image processing methods, segmentation techniques, feature extraction, and pattern recognition using Fourier transform, spatial filters, and artificial neural networks. This course emphasizes on mastering the latest technology and analytical skills to develop innovative solutions in the fields of health, transportation, and creative industries. By utilizing modern software and algorithms, students are expected to be able to design and implement image processing-based systems that support sustainable research and practical applications.

The Deep Learning course discusses concepts, methods, and techniques in the development of deep learning models for various artificial intelligence applications. Students will learn artificial neural network architecture, model optimization, transfer learning techniques, as well as deep learning applications in fields such as computer vision, natural language processing, and data analysis. The scope of the course includes the exploration of models such as Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Transformers, and Generative Adversarial Networks (GANs), with implementation using current frameworks such as TensorFlow and PyTorch.

This course aims to provide an in-depth understanding of the concepts and techniques of large-scale data analysis. Students will learn big data infrastructure, distributed data processing, data exploration techniques, and machine learning methods used in big data analytics. The scope includes technologies such as Hadoop, Spark, NoSQL, as well as the application of data analytics in business, healthcare, and intelligent systems.

This course discusses the theory and implementation of information retrieval systems used in searching and extracting information from various data sources. Students will learn search models such as Boolean, Vector, and Probabilistic, document ranking techniques, indexation, as well as the application of retrieval systems in search engines, recommender systems, and text analysis.

The Cyber Forensics course covers techniques and methodologies in digital crime investigation. Students will learn the process of collecting, analyzing, and interpreting digital evidence in various platforms, including operating systems, networks, and mobile devices. The scope includes forensic acquisition techniques, log analysis, malware identification, as well as legal and ethical aspects in cyber forensics.

This course focuses on principles, techniques, and patterns in designing and developing efficient and scalable software architectures. Students will learn software design concepts, component-based architecture management, microservices, and software quality evaluation. The scope of the course includes the application of design patterns, DevOps, and architecture documentation.

This course discusses strategies, methodologies, and techniques in managing change and projects in the field of information technology. Students will learn Agile approaches, Scrum, and traditional project management methods to ensure the successful implementation of technology in organizations. The scope of the course includes risk identification, stakeholder management, and IT project adoption and evaluation strategies.

The Thesis Proposal course at the masterÂ’s degree of the Informatics Study Program aims to provide an in-depth understanding of the process of preparing a quality research proposal, in accordance with academic guidelines. The focus of this course is to guide students in designing research, formulating research problems, conducting literature reviews, determining appropriate methodologies, and compiling comprehensive thesis proposals. The scope of this course includes an understanding of the proposal structure, data analysis techniques, and the preparation of relevant research reports in the field of informatics. The assessment in this course is based on the suitability of the format, structure, and substance of the thesis proposal produced by the students.

The Research Instrument Development course at the master degree of the Informatics Study Program aims to provide an in-depth understanding of the principles, theories, and techniques of developing valid and reliable research instruments. The focus of learning includes measurement theory, basic principles of instrument development, and validity and reliability techniques used in research. Students will be invited to design, develop, and test research instruments practically, by adjusting the needs in Informatics studies. The course also emphasizes the application of instrument development relevant to the context of Informatics study, including system performance measurement, data analysis, and technology evaluation.

This course is designed to equip students with skills in presenting research results academically. Students will learn scientific writing techniques, preparation of research reports, and strategies for presenting research results in scientific seminars and conferences. The scope of the course includes making academic papers, effective presentation techniques, and preparation for publication in reputable journals or conferences.

The Publication course at the masterÂ’s degree of the Informatics Study Program aims to guide students in producing quality scientific publications, with outputs that include reputable indexed international journals (such as Scopus), other international journals, to Sinta indexed national journals. Students will learn techniques and strategies for writing scientific articles, editing, the peer-review process, and manuscript management for publication. The scope of this course includes mastering publication ethics, understanding copyright, and skills in preparing articles for journals, conferences, or books. In addition, students will also be directed to understand strategies to increase the visibility and impact of scientific publications in Informatics.

The thesis course at the master degree of the Informatics Study Program aims to guide students in completing independent research as a requirement for graduation and obtaining a master's degree. Students will utilize the competencies gained from compulsory and elective courses to conduct in-depth research in the specific field that has been chosen. The main focus of this course is to produce new knowledge contributions through quality research and compile a thesis report that meets academic standards. The scope of this course includes the selection of research topics, problem formulation, application of research methods, data collection and analysis, to the preparation of a comprehensive thesis report ready to be tested by supervisors and examiners.