We are excited to announce the publication of two new edited books from IGI Global that explore the intersection of artificial intelligence, data science, and sustainability:

1. Artificial Intelligence and Data Science for Sustainability: Applications and Methods This book presents cutting-edge research on leveraging AI and data science to address sustainability challenges. It covers areas such as structural optimization, drone imagery, and development financing, offering insights for scholars, policymakers, and practitioners.

2. Achieving Sustainability in Multi-Industry Settings With AI This book explores the application of AI across various industries to promote sustainable practices. Topics include consumer protection, energy distribution, and smart cities, making it a valuable resource for professionals and researchers in computer science, engineering, and urban planning.

We are pleased to share that both edited books have been indexed by Scopus: Artificial Intelligence and Data Science for Sustainability: Applications and Methods (http://www.scopus.com/inward/record.url?eid=2-s2.0-85218110350&partnerID=MN8TOARS) and Achieving Sustainability in Multi-Industry Settings With AI (http://www.scopus.com/inward/record.url?eid=2-s2.0-105004508213&partnerID=MN8TOARS), enhancing its visibility and accessibility to the global research community.

We extend our heartfelt thanks to all authors, reviewers, and the publisher for their invaluable support throughout the publication and editing process.

Get this book​

Both books are now available through

• IGI Global's platform.
  🔗 Artificial Intelligence and Data Science for Sustainability: Applications and Methods: https://doi.org/10.4018/979-8-3693-6829-9
  🔗 Achieving Sustainability in Multi-Industry Settings With AI: https://doi.org/10.4018/979-8-3373-2530-9
  

• Google Books
  🔗 Artificial Intelligence and Data Science for Sustainability: Applications and Methods: https://books.google.co.kr/books?id=C7xGEQAAQBAJ
  🔗 Achieving Sustainability in Multi-Industry Settings With AI: https://books.google.co.kr/books?id=IrBTEQAAQBAJ
  

Best wishes,
Muhammad Syafrudin (Sejong University, South Korea)
Norma Latif Fitriyani (Sejong University, South Korea)
Prof. Muhammad Anshari (Universiti Brunei Darussalam, Brunei Book Editors

(🇮🇩) Sekarang Sejong University, Seoul, Korea Selatan, resmi masuk dalam daftar Perguruan Tinggi Tujuan Luar Negeri (PTLN) untuk program Magister dan Doktor Beasiswa Afirmasi LPDP Tahun 2025 di SEMUA bidang studi (all subjects). 🏫✨ (Sumber: https://lpdp.kemenkeu.go.id/beasiswa/kebijakan-umum/)

Sejong University adalah universitas berkelas dunia dengan pencapaian luar biasa:

• Peringkat Dunia:
  • QS World Ranking: 396th 🌍 (Sumber: https://www.topuniversities.com/universities/sejong-university)
  • THE Ranking: 201–250th 📊 (Sumber: https://www.timeshighereducation.com/world-university-rankings/sejong-university)
• Peringkat #1 di Korea selama 2 tahun berturut-turut dalam Leiden Ranking 2024, yang menilai kualitas penelitian universitas secara global.
  (Sumber: https://en.sejong.ac.kr/eng/News.do?mode=view&articleNo=24460&article.offset=0&articleLimit=9)

Saya siap membantu mengusahakan LoA Unconditional dari Sejong University, Department of Artificial Intelligence (AI) and Data Science (DS) untuk calon pendaftar yang memenuhi seluruh persyaratan berikut:

🔹 Syarat Pendaftaran:​

1. Pilih program studi: Department of Artificial Intelligence and Data Science serta mencantumkan saya sebagai dosen pembimbing.
2. Sertifikat bahasa Inggris yang berlaku: (Sumber: https://sos.sejong.ac.kr/eng/admission/guide/grad1.do)
   • TOEFL IBT ≥ 71
   • NEW TEPS ≥ 327
   • IELTS ≥ 5.5
3. Lulusan dari jurusan terkait, seperti:
   • Computer Engineering, Computer Science, Informatics, Information Systems, Mathematics, Statistics, atau bidang riset yang berkaitan dengan AI, Data Science, dsb.
4. Kirimkan CV/Resume, Ijazah S1/S2, dan transkrip nilai ke email saya udin@sejong.ac.kr
   • Wajib mencantumkan kode "LPDP-SJU 2025" di subjek atau isi email sebagai tanda bahwa Anda sudah membaca dan memahami informasi ini.

📅 Tahapan Seleksi LPDP 2025:​

1. Pendaftaran Seleksi
   🗓 17 Januari – 17 Februari 2025

2. Seleksi Administrasi
   🗓 18 Februari – 6 Maret 2025

3. Pengumuman Hasil Seleksi Administrasi
   🗓 7 Maret 2025

💡 Tertarik mengetahui lebih lanjut tentang tim riset kami?​

Silakan kunjungi: s.aintlab.com/1

Jangan ragu untuk membagikan informasi ini kepada teman, rekan, atau siapa saja yang membutuhkan. Mari kita bantu lebih banyak orang meraih impian mereka!

Terima kasih, semoga sukses, dan sehat selalu! 🙏

Best regards,

Muhammad Syafrudin

Semoga informasi ini bermanfaat dan proses pendaftaran berjalan lancar. Boleh disebarluaskan ya! 🚀

한국어로 읽기: https://www.sejong.ac.kr/news/people/faculty.do?mode=view&articleNo=793994&article.offset=30&articleLimit=10

Dr. Muhammad Syafrudin's team from Sejong University, in collaboration with Professor Muhammad Rifqi Maarif's team from Universitas Tidar, Indonesia, has published a groundbreaking paper in Sustainable Development, a journal ranked in the top 0.8% globally.

The paper, titled “Tweeting Circular Economy: Unveiling Current Discourse Through Natural Language Processing” (DOI link), analyzes 389,575 circular economy (CE)-related tweets (2012–2022) using advanced NLP techniques. Key findings include public focus on waste management, recycling, and resource efficiency, along with opportunities for integrating emerging technologies like blockchain and IoT in CE strategies.

This collaboration stems from the 2023 Visiting Researcher Program at Tidar University. Dr. Syafrudin expressed gratitude to Professor Maarif’s team, emphasizing the importance of continued collaboration for impactful research.

Read the full study here: 10.1002/sd.3323.

You may request the full text for personal use via https://www.researchgate.net/publication/387478766_Tweeting_Circular_Economy_Unveiling_Current_Discourse_Through_Natural_Language_Processing

한국어로 읽기: https://www.sejong.ac.kr/news/people/faculty.do?mode=view&articleNo=793987&article.offset=40&articleLimit=10

Our research team, led by Dr. Syafrudin, has published a groundbreaking study in the prestigious journal Computers and Electronics in Agriculture (impact factor: 7.7, top 1.7% in its field). The paper introduces FLTrans-Net (Transformer-based Feature Learning Network), an innovative algorithm for accurately detecting wheat ears in challenging agricultural environments.

Traditional convolutional neural networks (CNNs) struggle with small or overlapping wheat ears, but FLTrans-Net addresses this with a multi-scale fusion block, transformer encoder, spatial attention block, and a lightweight RetinaNet detection block. The algorithm enhances detection accuracy and is optimized for resource-constrained devices, promising to improve agricultural efficiency significantly.

Dr. Syafrudin, a faculty member at Sejong University since 2022 and recognized in the 2024 Global Top 2% Scientists list (Stanford/Elsevier), expressed gratitude to collaborators from Our Lab, HITEC University, and Kaunas University of Technology. He stated, “FLTrans-Net represents a significant step forward in applying AI to real-world agricultural challenges. We will continue to innovate in this area.”

Read the full study here: 10.1016/j.compag.2024.109706.

You may request the full text for personal use via https://www.researchgate.net/publication/386742803_FLTrans-Net_Transformer-based_feature_learning_network_for_wheat_head_detection

Dear Colleagues,

Currently, we are in the process of editing a forthcoming book entitled "Artificial Intelligence and Data Science for Sustainability: Applications and Methods", to be published by IGI Global, an international publisher of progressive academic research.

We would like to take this opportunity to cordially invite you all to submit your work for consideration in this book. Recommended topics include, but are not limited to, the following:

1. AI or DS for Energy Efficiency and Renewable Energy Management
2. AI or DS-driven Smart Cities and Sustainable Urban Planning
3. AI or DS in Sustainable Agriculture and Food Production
4. AI or DS for Waste Management and Circular Economy
5. AI or DS for Sustainable Transportation and Logistics
6. AI or DS in Environmental Monitoring and Protection
7. Ethical Considerations and Responsible AI or DS for Sustainability

We are certain that your contribution on this topic and/or other related research areas would make an excellent addition to this book. Please visit https://www.igi-global.com/publish/call-for-papers/call-details/7584 for more details regarding this book and to submit your work. You may kindly use the following link to submit your proposed chapter: https://www.igi-global.com/publish/call-for-papers/submit/7584

Note: There are no submission or acceptance fees for chapters submitted to this book publication.

If you have any questions or concerns, please do not hesitate to contact us. Thank you very much for your consideration of this invitation, and I hope to hear from you soon.

Best wishes,
Dr. Muhammad Syafrudin, Sejong University, korea (udin@sejong.ac.kr)
Dr. Norma Latif Fitriyani, Sejong University, korea (norma@sejong.ac.kr)
Dr. Muhammad Anshari, Universiti Brunei Darussalam, bruneidarussalam (anshari.ali@ubd.edu.bn)
Book Editors

Kabar Baik bagi beasiswa LPDP hunters!!!!

Menurut laman berikut LPDP (https://bantuan.lpdp.kemenkeu.go.id/kb/articles/perguruan-tinggi-luar-negeri-tujuan-pendaftaran-beasiswa-tidak-ada-pada-daftar-lembaga-pengelo), bagi semua pendaftar LPDP (silakan dicroscek lagi dengan pihak LPDP langsung jika ragu) dapat memilih Perguruan Tinggi Tujuan dan/atau program studi/subjek diluar daftar Perguruan Tinggi Tujuan LPDP, dengan ketentuan hanya dapat memilih satu Perguruan Tinggi tujuan, wajib mengunggah LoA Unconditional dan bukti pendukung yang menunjukkan bahwa Perguruan Tinggi Tujuan memenuhi kriteria sebagai berikut:

1. unggulan terbaik berdasarkan lembaga/instansi profesi keahlian; atau
   
2. penilaian lembaga independen pemeringkat dunia yang kredibel dan memiliki reputasi baik.

Sejong University masuk di Ranking Dunia, QS=436th (https://www.topuniversities.com/universities/sejong-university), THE=251–300th (https://www.timeshighereducation.com/world-university-rankings/sejong-university)

Saya bersedia “mengusahakan untuk mendapatkan LoA Unconditional” dari Sejong University, Department of Artificial Intelligence (AI) and Data Science (DS), bagi calon pendaftar yang memenuhi semua persyaratan berikut:

1. Pilih “Department of Artificial Intelligence and Data Science” dan “Muhammad Syafrudin”(https://muhammadsyafrudin.com/id) sebagai dosen pembimbing.
   
2. Syarat sertifikat bahasa inggris >= TOEFL IBT: 71 / NEW TEPS: 327 / IELTS: 5.5
   
3. Lulusan computer engineering/computer science/informatics/information systems/mathematics/statistics/etc. dan atau bidang riset s1/s2 berkaitan dengan AI, Data Science, Big Data, etc.
   

Silahkan kirim “CV/Resume, Ijazah S1/&S2 dan transkrip nilai” to udin@sejong.ac.kr dan pastikan cantumkan kode “LPDP-SJU” di subjek atau isi email sebagai indikasi bahwa Anda sudah membaca dan paham dengan isi pengumuman ini.

Boleh dishare dan disebarluaskan~!!

Terimakasih dan salam sehat dan sukses selalu!!

Best regards,
Syafrudin

Pendaftaran LPDP 2024

• Tahap 1: 11 Januari – 12 Februari 2024
  
• Tahap 2: 19 Juni – 18 Juli 2024

Sumber: https://lpdp.kemenkeu.go.id/beasiswa/kebijakan-umum/

Dear All,

I am delighted to have been invited to be Panel Speaker of Digital Technology at World Scientific Forum of Indonesia (WSFI) 2023. During my session, I had the opportunity to share and discuss the digital technology projects we have been working on in South Korea. I was also very enthusiastic about the tour around Bali!

Check this video for the Highlights of World Scientific Forum of Indonesia (WSFI) 2023 in Bali, Indonesia

Thank you for the opportunity, and I look forward to future collaborations.

Best regards,
Muhammad Syafrudin

About WSFI: The World Scientific Forum of Indonesia (WSFI) is a transformative event driven by the Directorate General of Higher Education, Research, and Technology. A dynamic event that builds on the success of previous initiatives, bringing together global experts and Indonesian diaspora scientists. WSFI seeks to strengthen global collaborations, foster international research partnerships, and enhance academic networks within Indonesia’s tertiary institutions. This forum aims to create a sustainable academic ecosystem and facilitate industry-academia partnerships on both national and international fronts, encouraging joint publications, and marking a significant milestone in advancing Indonesian research and education. https://www.wsfi.co.id/about/

Dear All,

I am pleased to share that Ms. Ahyun and Ms. Sujin have won the 3rd place of the Intelligent Mechanism x Artificial Intelligence Joint Academic Festival Award.

Congratulations on this remarkable achievement! Your hard work, dedication, and talent have paid off, and I am proud of your accomplishment.

Please keep up the excellent work, and I look forward to hearing about your future successes.

Best regards,
Muhammad Syafrudin

My colleagues and I are guest editing a special issue "Application of Artificial Intelligence in Decision Making", which will be published continuously by Mathematics (ISSN 2227-7390) (SCIE JCR Q1). You are welcome to submit your work for this issue. The deadline is July 31, 2024, next year. If you have any questions or need an APC discount, feel free to contact me. Thank you.

Page for the special issue: https://www.mdpi.com/journal/mathematics/special_issues/G97O0GT4A9

Best regards,
Muhammad Syafrudin
Dr. Norma Latif Fitriyani
Guest Editors

Dear Colleagues,

We are pleased to inform you that our story about Oracle Academy has been published online. Please kindly check in the following links:

• English: https://academy.oracle.com/en/about-success-spotlight-syafrudin.html
• Korean: https://academy.oracle.com/ko/about-success-spotlight-syafrudin.html
• Bahasa Indonesia: https://academy.oracle.com/en/about-success-spotlight-syafrudin-indonesian.html

Thank you!

Dear Colleagues,

We are pleased to inform you that our edited "Metaverse Applications for New Business Models and Disruptive Innovation" book is now available online!

It is expected that the metaverse will be the next generation of the internet and its online activities and will serve as the foundation for a massive online business platform. Furthermore, it will alter people's behavior, which will have an impact on businesses' decisions to choose the metaverse as their primary business platform.

Metaverse Applications for New Business Models and Disruptive Innovation showcases the most recent developments in the metaverse and their implications for business and considers the challenges and best practices of implementing this technology in business. Covering topics such as augmented reality, economics, security, and business models, this reference work is ideal for business owners, managers, computer scientists, researchers, scholars, academicians, practitioners, educators, and students.

Citation: Anshari, M., Syafrudin, M., & Alfian, G. (Eds.). (2023). Metaverse Applications for New Business Models and Disruptive Innovation. IGI Global. https://doi.org/10.4018/978-1-6684-6097-9

Best wishes,
Prof. Muhammad Anshari (Universiti Brunei Darussalam, Brunei)
Muhammad Syafrudin (Sejong University, Korea)
Dr. Ganjar Alfian (Universitas Gadjah Mada, Indonesia)
Book Editors

My colleagues and I are guest editing a special issue “Applied Artificial Intelligence for Sustainability”, which will be published continuously by Sustainability (SSCI SCIE JCR Q2, Scopus SJR Q1). You are welcome to submit your work for this issue. The deadline is May 31, 2023, next year. If you have any questions or need an APC discount, feel free to contact me. Thank you.

Page for the special issue: https://www.mdpi.com/journal/sustainability/special_issues/Applied_AI

Best regards,
Muhammad Syafrudin
Dr. Ganjar Alfian
Dr. Norma Latif Fitriyani
Dr. Muhammad Anshari
Guest Editors

My colleagues and I are guest editing a special issue related to the application of #machinelearning and #IoT in industry, which will be published continuously by Computers (Scopus SJR Q2). You are welcome to submit your work for this issue. The deadline is September 1, 2023, next year. If you have any questions or need an APC discount, feel free to contact me. Thank you.

Page for the special issue: https://www.mdpi.com/journal/computers/special_issues/ML_IoT_2023

Best regards,
Muhammad Syafrudin
Dr. Ganjar Alfian
Dr. Norma Latif Fitriyani
Guest Editors

Dear Colleagues,

Currently, we are in the process of editing a forthcoming book entitled "Metaverse Applications for New Business Models and Disruptive Innovation", to be published by IGI Global, an international publisher of progressive academic research.

We would like to take this opportunity to cordially invite you all to submit your work for consideration in this book. We are certain that your contribution on this topic and/or other related research areas would make an excellent addition to this book. Please visit https://www.igi-global.com/publish/call-for-papers/call-details/5848 for more details regarding this book and to submit your work. You may kindly use the following link to submit a chapter: https://www.igi-global.com/publish/call-for-papers/submit/5848

If you have any questions or concerns, please do not hesitate to contact us. Thank you very much for your consideration of this invitation, and I hope to hear from you by 4th April 2022.

Best wishes,
Muhammad Anshari (Universiti Brunei Darussalam, #bruneidarussalam)
Muhammad Syafrudin (Sejong University, #korea)
Ganjar Alfian (Universitas Gadjah Mada (UGM), #indonesia)
Editors

Abstract

Predicting future blood glucose (BG) levels for diabetic patients will help them avoid potentially critical health issues. We demonstrate the use of machine learning models to predict future blood glucose levels given a history of blood glucose values as the single input parameter. We propose an Artificial Neural Network (ANN) model with time-domain attributes to predict blood glucose levels 15, 30, 45 and 60 min in the future. Initially, the model’s features are selected based on the previous 30 min of BG measurements before a trained model is generated for each patient. These features are combined with time-domain attributes to give additional inputs to the proposed ANN. The prediction model was tested on 12 patients with Type 1 diabetes (T1D) and the results were compared with other data-driven models including the Support Vector Regression (SVR), K-Nearest Neighbor (KNN), C4.5 Decision Tree (DT), Random Forest (RF), Adaptive Boosting (AdaBoost) and eXtreme Gradient Boosting (XGBoost) models. Our results show that the proposed BG prediction model that is based on an ANN outperformed all other models with an average Root Mean Square Error (RMSE) of 2.82, 6.31, 10.65 and 15.33 mg/dL for Prediction Horizons (PHs) of 15, 30, 45 and 60 min, respectively. Our testing showed that combining time-domain attributes into the input data resulted in enhanced performance of majority of prediction models. The implementation of proposed prediction model allows patients to obtain future blood glucose levels, so that the preventive alerts can be generated before critical hypoglycemic/ hyperglycemic events occur.

Published in: Biocybernetics and Biomedical Engineering
DOI: 10.1016/j.bbe.2020.10.004

Dr. Muhammad Syafrudin
Editorial Board
Journal link: ComTech

Abstract

Extracting information from individual risk factors provides an effective way to identify diabetes risk and associated complications, such as retinopathy, at an early stage. Deep learning and machine learning algorithms are being utilized to extract information from individual risk factors to improve early-stage diagnosis. This study proposes a deep neural network (DNN) combined with recursive feature elimination (RFE) to provide early prediction of diabetic retinopathy (DR) based on individual risk factors. The proposed model uses RFE to remove irrelevant features and DNN to classify the diseases. A publicly available dataset was utilized to predict DR during initial stages, for the proposed and several current best-practice models. The proposed model achieved 82.033% prediction accuracy, which was a significantly better performance than the current models. Thus, important risk factors for retinopathy can be successfully extracted using RFE. In addition, to evaluate the proposed prediction model robustness and generalization, we compared it with other machine learning models and datasets (nephropathy and hypertension–diabetes). The proposed prediction model will help improve early-stage retinopathy diagnosis based on individual risk factors.

Published in: Mathematics
DOI: 10.3390/math8091620

Abstract

Detecting self-care problems is one of important and challenging issues for occupational therapists, since it requires a complex and time-consuming process. Machine learning algorithms have been recently applied to overcome this issue. In this study, we propose a self-care prediction model called GA-XGBoost, which combines genetic algorithms (GAs) with extreme gradient boosting (XGBoost) for predicting self-care problems of children with disability. Selecting the feature subset affects the model performance; thus, we utilize GA to optimize finding the optimum feature subsets toward improving the model’s performance. To validate the effectiveness of GA-XGBoost, we present six experiments: comparing GA-XGBoost with other machine learning models and previous study results, a statistical significant test, impact analysis of feature selection and comparison with other feature selection methods, and sensitivity analysis of GA parameters. During the experiments, we use accuracy, precision, recall, and f1-score to measure the performance of the prediction models. The results show that GA-XGBoost obtains better performance than other prediction models and the previous study results. In addition, we design and develop a web-based self-care prediction to help therapist diagnose the self-care problems of children with disabilities. Therefore, appropriate treatment/therapy could be performed for each child to improve their therapeutic outcome.

Published in: Mathematics
DOI: 10.3390/math8091590