Focus and Scopes

Focus
The International Journal of Data Science (IJoDS) champions the advancement of data science by publishing high-quality, original research that explores its theory, methodologies, and diverse applications. Our core mission is to illuminate the entire data lifecycle—from collection and storage to processing, analysis, visualization, and interpretation. We place a significant emphasis on forging strong connections between foundational theoretical concepts and practical, real-world impact. IJoDS aims to be a premier international platform for researchers, academics, and practitioners to disseminate innovative work, addressing the evolving challenges and opportunities in our data-driven world and fostering a global understanding and application of data science.

Scope
The scope of IJoDS is intentionally broad and multidisciplinary, welcoming contributions that explore and innovate across a wide spectrum of data science. The journal seeks to cover key methodologies, diverse application domains, and various problem types. The specific areas of interest include:

Key Methodologies and Techniques:

• Machine Learning (e.g., supervised and unsupervised learning)
• Neural Networks and Deep Learning (e.g., CNN, RNN, LSTM)
• Data Mining and Knowledge Discovery
• Predictive Modeling, Classification, Regression, and Forecasting (including Time Series analysis)
• Optimization Algorithms
• Statistical Analysis and Modeling
• Big Data Analytics and Technologies
• Natural Language Processing (NLP), Text Mining, Sentiment Analysis, and Text Summarization
• Specific Algorithms (e.g., Support Vector Machines, Random Forests, Decision Trees, Clustering algorithms, Fuzzy Logic)
• Hybrid Methods combining various analytical techniques
• Systematic Literature Reviews (SLR) and Meta-Analyses on data science topics
• Computer Vision and Image Processing
• Expert Systems and Genetic Algorithms
• Graph Methods and Pattern Recognition

Primary Application Domains (but not limited to):

• Healthcare and Medicine (e.g., disease prediction and classification, patient monitoring, medical data analysis, cancer research, diabetes management)
• Education (e.g., student learning analytics, academic performance prediction, educational technology)
• Business and Finance (e.g., stock market prediction, customer behavior analysis, financial forecasting)
• Environmental Science (e.g., weather and climate prediction, environmental monitoring)
• Language Technology (e.g., analysis of textual data, including specific languages like Indonesian)
• Social Sciences and Digital Humanities (e.g., social media analysis, opinion mining, detection of hoaxes or cyberbullying)
• Technology and Engineering (e.g., applications in smart cities, IoT, industry processes)
• Agriculture, Government and Public Services, Tourism, and Supply Chain Management.

Types of Problems Addressed:
The journal publishes research that focuses on, but is not limited to:

• Prediction and Forecasting
• Classification and Detection
• Data Analysis, Interpretation, and Insights
• Optimization of Systems and Algorithms
• Pattern Identification and Recognition
• System Monitoring, Assessment, and Early Warning
• Recommendation Systems
• Data Summarization and Visualization
• Comparative Evaluation of methods, techniques, and tools
• Investigating the role, impact, and influence of data science across diverse sectors.

IJoDS encourages the submission of articles that present novel algorithms, innovative applications of existing techniques, significant case studies, comparative studies, and insightful systematic reviews that contribute to the advancement of data science theory and practice.

Journal Subject Classifications (ASJC Codes)
The International Journal of Data Science primarily covers subjects within the following All Science Journal Classification (ASJC) codes: