Applied Computing and Informatics

Aims & Scope

Applied Computing and Informatics aims to be timely in disseminating leading-edge knowledge to researchers, practitioners and academics whose interest is in the latest developments in applied computing and information systems concepts, strategies, practices, tools and technologies.

In particular, the journal encourages research studies that have significant contributions to make to the continuous development and improvement of IT practices in the Kingdom of Saudi Arabia and other countries.

By doing so, the journal attempts to bridge the gap between the academic and industrial community, and therefore, welcomes theoretically grounded, methodologically sound research studies that address various IT-related problems and innovations of an applied nature.

The journal will serve as a forum for practitioners, researchers, managers and IT policy makers to share their knowledge and experience in the design, development, implementation, management and evaluation of various IT applications.

Metrics & Ranking

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Directory of Open Access Journals (DOAJ)
• Web of Science

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, designed to support cutting-edge academic discovery.

Licensing & Copyright

This journal operates under an Open Access model. Articles are freely accessible to the public immediately upon publication. The content is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), allowing users to share and adapt the work with proper attribution.

Copyright remains with the author(s), and no permission is required for non-commercial use, provided the original source is cited.

Policy Links

This section provides access to essential policy documents, guidelines, and resources related to the journal’s publication and submission processes.

• Aims scope
• Homepage
• Oa statement
• Author instructions
• License terms
• Review url
• Board url
• Copyright url
• Preservation url
• Apc url
• License

APC Details

The journal’s Article Processing Charge (APC) policies support open access publishing in Computer Science, ensuring accessibility and quality in research dissemination.

This journal does not charge a mandatory Article Processing Charge (APC). However, optional open access publication may incur fees based on the publisher’s policies.

Explore journals without APCs for alternative publishing options.

Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Classification assessment methods

  Citation: 1429

  Authors: Alaa

• Predictive modelling and analytics for diabetes using a machine learning approach

  Citation: 202

  Authors: Harleen, Vinita

• Solar power generation forecasting using ensemble approach based on deep learning and statistical methods

  Citation: 145

  Authors: Mariam, Imtiaz

• Independent component analysis: An introduction

  Citation: 123

  Authors: Alaa

• A Mixed approach of Deep Learning method and Rule-Based method to improve Aspect Level Sentiment Analysis

  Citation: 117

  Authors: Paramita, Amlan

• Aspect-based sentiment analysis using smart government review data

  Citation: 115

  Authors: Omar, Nur, Azza, Khaled

• Artificial Neural Networks and Machine Learning techniques applied to Ground Penetrating Radar: A review

  Citation: 97

  Authors: Xisto L., Sérgio L., Nathan

• Enabling privacy and security in Cloud of Things: Architecture, applications, security & privacy challenges

  Citation: 81

  Authors: Ado Adamou, Olga Kengni, Chafiq, Ousmane, Alidou, Abdelhak Mourad

• Hybrid binary bat enhanced particle swarm optimization algorithm for solving feature selection problems

  Citation: 79

  Authors: Mohamed A., Kevin B.

• Occupancy detection in non-residential buildings – A survey and novel privacy preserved occupancy monitoring solution

  Citation: 65

  Authors: J., H., R., M., A.