Sosyal Nesnelerin İnternetinden Kaynaklanan Büyük Verilerin Doğruluğu ve Gerçekliğinin Tespiti için ML Algoritmalarıyla Veri Ön İşleme Yaklaşımı ve Bir Vaka Çalışması
Öz
IoT, çevremizdeki sayısız fiziksel olayı algılayan, bunları veriye dönüştüren ve bu verileri farklı ortamlara veya dijital sistemlere aktaran sensörler dünyasıdır. Nesnelerin İnterneti tabanlı teknolojilerin kullanım alanları sürekli artmakta ve IoT altyapısını destekleyecek teknolojiler geliştirilmektedir. Ancak algılama katmanında üretilen büyük miktardaki büyük verinin etkin bir şekilde yönetilebilmesi için ön işleme tabi tutulması ve büyük veri standartlarıyla uyumlu hale getirilmesi gerekmektedir. Büyük verinin etkin bir şekilde yönetilebilmesi için veri seti standartlarının iyileştirilmesi gerekmekte ve daha kaliteli bir veri seti için farklı veri işleme yöntemleri geliştirilmektedir. Bu çalışmada, mobil cihazlar kullanılarak IoT algılama katmanında üretilen verilerin doğruluğu ve güvenilirliğini belirlemek amacıyla literatür taraması yapılmıştır. Ayrıca çalışmada, mobil cihazlar ve sosyal platformlar üzerinde üretilen verilerden oluşan veri seti ML sınıflandırma algoritmaları ile incelenmiştir. Veri seti üzerinde Lojistik Regresyon (LR), Naive Bayes (NB), Rastgele Orman (RF), K-en yakın komşu (kNN), Destek Vektör Makineleri (SVM) sınıflandırma algoritmaları ile doğruluk ve güvenilirlik açısından karşılaştırmalar ve değerlendirmeler yapılmıştır. ML sınıflandırma algoritmaları üzerinde yapılan çalışmalar sonucunda, Rastgele Orman ve Destek Vektör Makineleri algoritmalarının yakın oranlarda doğruluk sağladığı görülmektedir. Bu çalışma, IoT algılama katmanında mobil cihazlar kullanılarak elde edilen verilerin doğruluğunu ve güvenilirliğini artırmak için etkili algoritmaların belirlenmesine katkıda bulunmaktadır.
Anahtar Kelimeler
Nesnelerin İnterneti Sosyal Nesnelerin İnterneti Büyük Veri Veri işleme
Kaynakça
- [1] Shahab, S., Agarwal, P., Mufti, T., & Obaid, A. J. (2022). SIoT (Social Internet of Things): A Review. Evolutionary Computing and Mobile Sustainable Networks, 313–323.
- [2] Dhelim, S., Ning, H., Farha, F., Chen, L., Atzori, L., & Daneshmand, M. (2021). IoT-Enabled Social Relationships Meet Artificial Social Intelligence. IEEE Internet of Things Journal, 8(20), 15364–15375.
- [3] Nejad, H. V., Farimani, Z. M., & Tavakolifar, A. (2020). Social Internet of Things and New Generation Computing—A Survey. Toward Social Internet of Things (SIoT), 846, 129–152.
- [4] Kaya, Ş. M., & Kaya, E. (2022). The (Un)seen Influence of S-IoT on the Political Economic Decisions. In 6th International Congress of Social Sciences, Istanbul.
- [5] Rad, M. M., Rahmani, A. M., Sahafi, A., & Qader, N. N. (2020). Social Internet of Things: vision, challenges, and trends. Human-centric Computing and Information Sciences, 10.
- [6] Kaur, N., & Sood, S. K. (2023). Social Internet of Things (SIoT): A decade’s journey and future directions. Journal of Network and Computer Applications, 210.
- [7] Dhelim, S., Ning, H., Farha, F., Chen, L., Atzori, L., & Daneshmand, M. (2021). IoT-Enabled Social Relationships Meet Artificial Social Intelligence. IEEE Internet of Things Journal, 8(20), 15364–15375.
- [8] İşler, B., Kaya, Ş. M., & Kılıç, F. R. (2025). Fog-Enabled Machine Learning Approaches for Weather Prediction in IoT Systems: A Case Study. Sensors, 25(13), 4070.
- [9] Zhang, L., et al. (2021). Integrating Social Media Data with IoT for Enhanced User Experience. IEEE Internet of Things Journal, 8(3), 1540–1552.
- [10] Kim, J., et al. (2020). Understanding User Characteristics and Interactions on Social Media Platforms. Journal of Interactive Advertising, 20(3).
- [11] Chen, M., et al. (2019). Trust management in social Internet of Things: A survey. IEEE Communications Surveys & Tutorials, 22(2), 1197–1230.
- [12] Li, J., & Wang, H. (2020). A sentiment-aware framework for social IoT applications based on hybrid machine learning. Future Generation Computer Systems, 108, 512–524.
- [13] Gupta, R., et al. (2022). Real-time analytics for social IoT using edge computing. IEEE Transactions on Network and Service Management, 19(1), 67–80.
- [14] Zhou, J., Leung, V. C., & Yang, L. T. (2021). Internet of Things security and privacy: Challenges and solutions. IEEE Internet of Things Journal, 8(12), 10231–10255.
- [15] Kaya, Ş. M. (2025). Edge And Fog Computing With Artificial Intelligence Methods On Iot-Based Big Data. Artificial Intelligence: Foundations, Applications and Future Directions, 347.
- [16] Johnson, E. (2019). IoT Sensors and Their Applications in Smart Systems. Sensors and Actuators B: Chemical, 185, 230–245.
- [17] Hatton, M. (2013, January). The global M2M market in 2013. Machina Research White Paper.
- [18] Gahi, Y., Guennoun, M., & Mouftah, H. T. (2016). Big Data Analytics: Security and Privacy Challenges. In Proceedings of the 2016 IEEE Symposium on Computers and Communication (ISCC) (pp. 952–957). Messina, Italy.
- [19] Zikopoulos, I., Eaton, C. P., & Zikopoulos, P. (2011). Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data (1st ed.). McGraw-Hill Osborne Media.
- [20] Schneider, R. D. (2012). Hadoop for Dummies (Special ed.). John Wiley & Sons.
- [21] Setty, K., & Bakhshi, R. (2013). What Is Big Data and What Does It Have to Do with IT Audit?. ISACA Journal, 3, 23–25.
- [22] Kaya, Ş. M., Bayram, V., & Özkan, M. (2025). Evaluation of the intergenerational relationship of IoT awareness in businesses. Journal of Information and Optimization Sciences, 46(5), 1753–1772.
- [23] Cyganek, B., et al. (2016). A Survey of Big Data Issues in Electronic Health Record Analysis. Applied Artificial Intelligence, 30(6), 497–520.
- [24] Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137–144.
- [25] Zhang, L., et al. (2021). Integrating Social Media Data with IoT for Enhanced User Experience. IEEE Internet of Things Journal, 8(3), 450–465.
- [26] Esmaili Jobani, A., & Kaya, Ş. M. (2025). Hybrid IoT and AI-based Solution for Energy Management in Data Centres under Various Climate Conditions. Anadolu Bil Meslek Yüksekokulu Dergisi, 20(72), 107–124.
- [27] Chen, Y., et al. (2019). Analyzing User Behavior on Social Media Platforms: Methods and Applications. ACM Transactions on Social Computing, 4(2), 75–90.
- [28] Smith, E., et al. (2018). User Characteristics and Interactions on Social Media Platforms: Insights from Data Analytics. International Journal of Information Management, 45, 210–225.
- [29] Hancke, G. P., & Hancke Jr., G. P. (2013). The role of advanced sensing in smart cities. Sensors, 13(1), 393–425.
- [30] Talari, S., et al. (2017). A Review of Smart Cities Based on the Internet of Things Concept. Energies, 10(4), 421.
- [31] Sikder, A. K., Petracca, G., Aksu, H., Jaeger, T., & Uluagac, A. S. (2018). A Survey on Sensor-Based Threats to Internet-of-Things (IoT) Devices and Applications. ArXiv Preprint.
- [32] Kaya, Ş. M., Erdem, A., & Güneş, A. (2021). A Smart Data Pre-Processing Approach to Effective Management of Big Health Data in IoT Edge. Smart Homecare Technology and TeleHealth, 9–21.
- [33] Kaya, Ş. M., İşler, B., Abu-Mahfouz, A. M., Rasheed, J., & AlShammari, A. (2023). An Intelligent Anomaly Detection Approach for Accurate and Reliable Weather Forecasting at IoT Edges: A Case Study. Sensors, 23(5), 2426.
- [34] Ahmed, I., Saeed, A., & Malik, H. (2023). A trust-aware data filtering framework for Social Internet of Things. Computer Networks, 225, 109554.
- [35] Kaya, Ş. M., Erdem, A., & Güneş, A. (2022). Anomaly Detection and Performance Analysis by Using Big Data Filtering Techniques For Healthcare on IoT Edges. Sakarya University Journal of Science, 26(1), 1–13.
- [36] Li, S., Raymond, K. K., Sun, Q., Buchanan, W. J., & Cao, J. (2015). IoT Forensics: Amazon Echo as a Use Case. Journal of Latex Class Files, 14.
- [37] James, G., Witten, D., Hastie, T., & Tibshirani, R. (2021). An Introduction to Statistical Learning: with Applications in R (2nd ed.). Springer.
- [38] Bayram, V., & Kaya, M. (2023). The Contributions of Metaverse Technology on Management Information Systems in Strategic Planning and Decision-Making Processes of Businesses. Uluslararası Yönetim Akademisi Dergisi, 6(3), 794–807.
- [39] Tharwat, A. (2021). Classification assessment methods. Applied Computing and Informatics, 17(1), 168–192
- [40] Kaya, Ş. M., & Bayram, V. (2025). Artificial Intelligence Awareness Scale Development Study. OPUS Journal of Society Research, 22(4), 657–672.
- [41] Cihan, P. (2018). Determination of diagnosis, prognosis and risk factors in animal diseases using by data mining methods. PhD Thesis, Yildiz Technical University, Istanbul, Turkey.
Data Pre-processing Approach with ML Algorithms for Accuracy and Authenticity Detection of Big Data Sourced from the Social Internet of Things and a Case Study
Öz
The Social Internet of Things (SIoT), which integrates sensor data with social media interactions, produces massive volumes of unstructured data that require accurate and reliable preprocessing for meaningful analysis. This study investigates the effectiveness of various machine learning (ML) classification algorithms in detecting the accuracy and authenticity of SIoT-derived data.A dataset comprising 17,500 user records collected from mobile devices and social media platforms was analyzed using five ML classifiers: Logistic Regression, Naive Bayes, K-Nearest Neighbor (K-NN), Random Forest, and Support Vector Machines (SVM). Through extensive hyperparameter tuning and 5-fold cross-validation, the Random Forest and SVM models exhibited the highest performance, achieving accuracy scores of 0.58 and 0.57, respectively. SVM also obtained the best AUC value of 0.64, highlighting its strength in distinguishing authentic from manipulated data. Additionally, the results emphasize the need for larger, more diverse datasets, and suggest incorporating deep learning and automated bias mitigation methods in future research.
Anahtar Kelimeler
Internet of Things Social Internet of Things Big Data Data Processing
Kaynakça
- [1] Shahab, S., Agarwal, P., Mufti, T., & Obaid, A. J. (2022). SIoT (Social Internet of Things): A Review. Evolutionary Computing and Mobile Sustainable Networks, 313–323.
- [2] Dhelim, S., Ning, H., Farha, F., Chen, L., Atzori, L., & Daneshmand, M. (2021). IoT-Enabled Social Relationships Meet Artificial Social Intelligence. IEEE Internet of Things Journal, 8(20), 15364–15375.
- [3] Nejad, H. V., Farimani, Z. M., & Tavakolifar, A. (2020). Social Internet of Things and New Generation Computing—A Survey. Toward Social Internet of Things (SIoT), 846, 129–152.
- [4] Kaya, Ş. M., & Kaya, E. (2022). The (Un)seen Influence of S-IoT on the Political Economic Decisions. In 6th International Congress of Social Sciences, Istanbul.
- [5] Rad, M. M., Rahmani, A. M., Sahafi, A., & Qader, N. N. (2020). Social Internet of Things: vision, challenges, and trends. Human-centric Computing and Information Sciences, 10.
- [6] Kaur, N., & Sood, S. K. (2023). Social Internet of Things (SIoT): A decade’s journey and future directions. Journal of Network and Computer Applications, 210.
- [7] Dhelim, S., Ning, H., Farha, F., Chen, L., Atzori, L., & Daneshmand, M. (2021). IoT-Enabled Social Relationships Meet Artificial Social Intelligence. IEEE Internet of Things Journal, 8(20), 15364–15375.
- [8] İşler, B., Kaya, Ş. M., & Kılıç, F. R. (2025). Fog-Enabled Machine Learning Approaches for Weather Prediction in IoT Systems: A Case Study. Sensors, 25(13), 4070.
- [9] Zhang, L., et al. (2021). Integrating Social Media Data with IoT for Enhanced User Experience. IEEE Internet of Things Journal, 8(3), 1540–1552.
- [10] Kim, J., et al. (2020). Understanding User Characteristics and Interactions on Social Media Platforms. Journal of Interactive Advertising, 20(3).
- [11] Chen, M., et al. (2019). Trust management in social Internet of Things: A survey. IEEE Communications Surveys & Tutorials, 22(2), 1197–1230.
- [12] Li, J., & Wang, H. (2020). A sentiment-aware framework for social IoT applications based on hybrid machine learning. Future Generation Computer Systems, 108, 512–524.
- [13] Gupta, R., et al. (2022). Real-time analytics for social IoT using edge computing. IEEE Transactions on Network and Service Management, 19(1), 67–80.
- [14] Zhou, J., Leung, V. C., & Yang, L. T. (2021). Internet of Things security and privacy: Challenges and solutions. IEEE Internet of Things Journal, 8(12), 10231–10255.
- [15] Kaya, Ş. M. (2025). Edge And Fog Computing With Artificial Intelligence Methods On Iot-Based Big Data. Artificial Intelligence: Foundations, Applications and Future Directions, 347.
- [16] Johnson, E. (2019). IoT Sensors and Their Applications in Smart Systems. Sensors and Actuators B: Chemical, 185, 230–245.
- [17] Hatton, M. (2013, January). The global M2M market in 2013. Machina Research White Paper.
- [18] Gahi, Y., Guennoun, M., & Mouftah, H. T. (2016). Big Data Analytics: Security and Privacy Challenges. In Proceedings of the 2016 IEEE Symposium on Computers and Communication (ISCC) (pp. 952–957). Messina, Italy.
- [19] Zikopoulos, I., Eaton, C. P., & Zikopoulos, P. (2011). Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data (1st ed.). McGraw-Hill Osborne Media.
- [20] Schneider, R. D. (2012). Hadoop for Dummies (Special ed.). John Wiley & Sons.
- [21] Setty, K., & Bakhshi, R. (2013). What Is Big Data and What Does It Have to Do with IT Audit?. ISACA Journal, 3, 23–25.
- [22] Kaya, Ş. M., Bayram, V., & Özkan, M. (2025). Evaluation of the intergenerational relationship of IoT awareness in businesses. Journal of Information and Optimization Sciences, 46(5), 1753–1772.
- [23] Cyganek, B., et al. (2016). A Survey of Big Data Issues in Electronic Health Record Analysis. Applied Artificial Intelligence, 30(6), 497–520.
- [24] Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137–144.
- [25] Zhang, L., et al. (2021). Integrating Social Media Data with IoT for Enhanced User Experience. IEEE Internet of Things Journal, 8(3), 450–465.
- [26] Esmaili Jobani, A., & Kaya, Ş. M. (2025). Hybrid IoT and AI-based Solution for Energy Management in Data Centres under Various Climate Conditions. Anadolu Bil Meslek Yüksekokulu Dergisi, 20(72), 107–124.
- [27] Chen, Y., et al. (2019). Analyzing User Behavior on Social Media Platforms: Methods and Applications. ACM Transactions on Social Computing, 4(2), 75–90.
- [28] Smith, E., et al. (2018). User Characteristics and Interactions on Social Media Platforms: Insights from Data Analytics. International Journal of Information Management, 45, 210–225.
- [29] Hancke, G. P., & Hancke Jr., G. P. (2013). The role of advanced sensing in smart cities. Sensors, 13(1), 393–425.
- [30] Talari, S., et al. (2017). A Review of Smart Cities Based on the Internet of Things Concept. Energies, 10(4), 421.
- [31] Sikder, A. K., Petracca, G., Aksu, H., Jaeger, T., & Uluagac, A. S. (2018). A Survey on Sensor-Based Threats to Internet-of-Things (IoT) Devices and Applications. ArXiv Preprint.
- [32] Kaya, Ş. M., Erdem, A., & Güneş, A. (2021). A Smart Data Pre-Processing Approach to Effective Management of Big Health Data in IoT Edge. Smart Homecare Technology and TeleHealth, 9–21.
- [33] Kaya, Ş. M., İşler, B., Abu-Mahfouz, A. M., Rasheed, J., & AlShammari, A. (2023). An Intelligent Anomaly Detection Approach for Accurate and Reliable Weather Forecasting at IoT Edges: A Case Study. Sensors, 23(5), 2426.
- [34] Ahmed, I., Saeed, A., & Malik, H. (2023). A trust-aware data filtering framework for Social Internet of Things. Computer Networks, 225, 109554.
- [35] Kaya, Ş. M., Erdem, A., & Güneş, A. (2022). Anomaly Detection and Performance Analysis by Using Big Data Filtering Techniques For Healthcare on IoT Edges. Sakarya University Journal of Science, 26(1), 1–13.
- [36] Li, S., Raymond, K. K., Sun, Q., Buchanan, W. J., & Cao, J. (2015). IoT Forensics: Amazon Echo as a Use Case. Journal of Latex Class Files, 14.
- [37] James, G., Witten, D., Hastie, T., & Tibshirani, R. (2021). An Introduction to Statistical Learning: with Applications in R (2nd ed.). Springer.
- [38] Bayram, V., & Kaya, M. (2023). The Contributions of Metaverse Technology on Management Information Systems in Strategic Planning and Decision-Making Processes of Businesses. Uluslararası Yönetim Akademisi Dergisi, 6(3), 794–807.
- [39] Tharwat, A. (2021). Classification assessment methods. Applied Computing and Informatics, 17(1), 168–192
- [40] Kaya, Ş. M., & Bayram, V. (2025). Artificial Intelligence Awareness Scale Development Study. OPUS Journal of Society Research, 22(4), 657–672.
- [41] Cihan, P. (2018). Determination of diagnosis, prognosis and risk factors in animal diseases using by data mining methods. PhD Thesis, Yildiz Technical University, Istanbul, Turkey.
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Konular | Yazılım Mimarisi, Yazılım Testi, Doğrulama ve Validasyon |
| Bölüm | Araştırma Makalesi |
| Yazarlar | |
| Gönderilme Tarihi | 3 Haziran 2025 |
| Kabul Tarihi | 3 Aralık 2025 |
| Yayımlanma Tarihi | 28 Mart 2026 |
| DOI | https://doi.org/10.17694/bajece.1712376 |
| IZ | https://izlik.org/JA76SC34AK |
| Yayımlandığı Sayı | Yıl 2026 Cilt: 14 |
Kaynak Göster
Amaç ve Kapsam
Balkan Journal of Electrical and Computer Engineering - (BAJECE)
(An International Peer Reviewed, indexed and Open Access Journal)
The journal publishes original papers in the extensive field of Electrical-electronics and Computer engineering. It accepts contributions which are fundamental for the development of electrical engineering and its applications, including overlaps to physics. Manuscripts on both theoretical and experimental work are welcome. Review articles and letters to the editors are also included.
Application areas include (but are not limited to):
Electrical & Electronics Engineering
Computer Engineering
Software Engineering
Biomedical Engineering
Electrical Power Engineering
Electric analysis & Mathematical models.
Electrical Control Engineering
Signal and Image Processing
Communications
Networking
Sensors, Actuators, Remote sensing, Consumer electronics, Fiber optics
Radar and Sonar systems
Artificial Intelligence and its Applications, Expert Systems
Medical imaging, Biomedical analysis and its applications
Computer vision, Pattern recognition,
Robotics, industrial automation
Renewable Energy
Yazım Kuralları
IMPORTANT INFORMATION FOR AUTHORS
Manuscript will be considered only on the understanding that it is not currently being submitted to other journals.
Submission of an article implies that the results described has not been published previously (except in the form of an abstract or as part of a published lecture or academic thesis), that it is not under consideration for publication elsewhere, that its publication is approved by all authors and that, if accepted, it will not be published elsewhere in the same form, in English or in any other language, without the written consent of the Publisher.
Authors are obliged to follow remarks and comments of the reviewers, as well as to follow Instructions for preparing manuscripts and technical remarks and corrections of the Editorial Board.
Papers will be published in English, and authors are obliged to submit papers free of typing errors (please use Spell Checking).
Editorial Board has right to make small lector corrections and to shorten text of the paper, which would not influence author's ideas and presentation. After computer lay-out of the paper, authors will obtain text as .pdf file for approval.
The manuscripts, not exceeding 12 pages (for review papers maximum 20 pages), including figures and tables, should be submitted in electronic form only in MS Word (.doc file) or LaTex format (.tex file), and submit to submission system.
For each author full name, personal (or first) name(s) and family (or last) name(s), and affiliation, have to be given. Family or last name(s) has to be written in capital letters. In the case of more than one author, the name of corresponding author should be indicated, with full postal address, e-mail address, and affiliation.
Each paper has to be written according to following order: title, author(s), affiliation(s), abstract, key words, body of the text with numerated sections and subsections including introduction, conclusions, acknowledgment (if necessary), nomenclature, and references. Pages must have page numbers.
Each author and coauthor have the possibility to subscribe for 10 reprints of their paper (for details, see our subscription page).
Authors note that paper can not be withdrawn at any condition once it is accepted. The Authors may not publish his/her The Author may not publish his/her contribution anywhere else without the prior written permission of the publisher unless it has been changed substantially. The Author warrants that his/her contribution is original, except for such excerpts from copyrighted works as may be included with the permission of the copyright holder and author thereof, that it contains no libellous statements, and does not infringe on any copyright, trademark, patent, statutory right, or propriety right of others. The Author signs for and accepts responsibility for releasing this material on behalf of any and all co-authors. In return for these rights:
All proprietary rights other than copyrights, such as patent rights.
The right to use all or part of this article, including tables and figures in future works of their own, provided that the proper acknowledgment is made to the Publisher as copyright holder.
The right to make copies of this article for his/her own use, but not for sale.
It is the responsibility of each author to ensure that papers submitted to the journal are written with ethical standards in mind, concerning plagiarism. Please note that all submissions are thoroughly checked for plagiarism. If an attempt at plagiarism is found in a published paper, the authors will be asked to issue a written apology to the authors of the original material. Any paper which shows obvious signs of plagiarism will be automatically rejected and its authors may be banned for duration of 10 years from publishing in Journal. The authors will receive proper notification if such a situation arises.
This paper has not been published in the same form elsewhere.
It will not be submitted anywhere else for publication prior to acceptance/rejection by BAJECE.
Ethics;
Papers must be submitted on the understanding that they have not been published elsewhere and are not currently under consideration by another journal. The submitting author is responsible for ensuring that the article’s publication has been approved by all the other coauthors. When an author discovers a significant error or inaccuracy in his/her own published work, it is the author's obligation to notify the publisher and cooperate with the editor to retract or correct the paper. It is also the authors’ responsibility to ensure that the articles emanating from a particular institution are submitted with the approval of the necessary institution. Only an acknowledgment from the editorial office officially establishes the date of receipt. Further correspondence and proofs will be sent to the author(s) before publication unless otherwise indicated. It is a condition of submission of a paper that the authors permit editing of the paper for readability.
BAJECE is committed to following the Code of Conduct and Best Practice Guidelines of COPE (Committee on Publication Ethics) . It is a duty of our editors to follow Cope Guidance for Editors and our peer-reviewers must follow COPE Ethical Guidelines for Peer Reviewers .
If you have any questions, please contact the relevant editorial office, or Balkan Journal of Electrical and Computer Engineering (BAJECE)' ethics representative: bajece@hotmail.com
Download a PDF version of the Ethics and Policies [PDF,392KB].
Reviewer Process Information
BAJECE employs a single-blind peer review process to ensure scientific quality, fairness, and transparency. In this review model, reviewers are able to see the authors’ names and affiliations, while authors do not have access to the reviewers’ identities. This approach allows reviewers to provide objective, detailed, and constructive feedback while maintaining their anonymity.
All submitted manuscripts are first evaluated by the Editorial Board for relevance, structure, and adherence to journal guidelines. Papers that meet the initial criteria are then assigned to at least two independent reviewers who are experts in the related research area. Reviewers assess manuscripts based on originality, technical accuracy, clarity, methodology, and scientific contribution.
Authors are required to revise their papers according to reviewers’ comments and suggestions within the given time frame. The final publication decision—acceptance, revision, or rejection—is made by the Editor-in-Chief after considering the reviewers’ recommendations and the scientific merit of the manuscript.
This single-blind review process ensures impartial evaluation, promotes academic integrity, and supports high-quality scientific publication standards in BAJECE.
Etik İlkeler ve Yayın Politikası
Papers must be submitted on the understanding that they have not been published elsewhere and are not currently under consideration by another journal. The submitting author is responsible for ensuring that the article’s publication has been approved by all the other coauthors. When an author discovers a significant error or inaccuracy in his/her own published work, it is the author's obligation to notify the publisher and cooperate with the editor to retract or correct the paper. It is also the authors’ responsibility to ensure that the articles emanating from a particular institution are submitted with the approval of the necessary institution. Only an acknowledgment from the editorial office officially establishes the date of receipt. Further correspondence and proofs will be sent to the author(s) before publication unless otherwise indicated. It is a condition of submission of a paper that the authors permit editing of the paper for readability.
BAJECE is committed to following the Code of Conduct and Best Practice Guidelines of COPE (Committee on Publication Ethics) . It is a duty of our editors to follow Cope Guidance for Editors and our peer-reviewers must follow COPE Ethical Guidelines for Peer Reviewers .
If you have any questions, please contact the relevant editorial office, or Balkan Journal of Electrical and Computer Engineering (BAJECE)' ethics representative: bajece@hotmail.com
Download a PDF version of the Ethics and Policies [PDF,392KB].
Reviewer Process Information
BAJECE employs a single-blind peer review process to ensure scientific quality, fairness, and transparency. In this review model, reviewers are able to see the authors’ names and affiliations, while authors do not have access to the reviewers’ identities. This approach allows reviewers to provide objective, detailed, and constructive feedback while maintaining their anonymity.
All submitted manuscripts are first evaluated by the Editorial Board for relevance, structure, and adherence to journal guidelines. Papers that meet the initial criteria are then assigned to at least two independent reviewers who are experts in the related research area. Reviewers assess manuscripts based on originality, technical accuracy, clarity, methodology, and scientific contribution.
Authors are required to revise their papers according to reviewers’ comments and suggestions within the given time frame. The final publication decision—acceptance, revision, or rejection—is made by the Editor-in-Chief after considering the reviewers’ recommendations and the scientific merit of the manuscript.
This single-blind review process ensures impartial evaluation, promotes academic integrity, and supports high-quality scientific publication standards in BAJECE.
Ücret Politikası
Dizinler
Dergi Kurulları
All articles published by BAJECE are licensed under the Creative Commons Attribution 4.0 International License. This permits anyone to copy, redistribute, remix, transmit and adapt the work provided the original work and source is appropriately cited.Creative Commons Lisans