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All Journal Jurnal Kolaboratif Sains Journal of Current Studies in SDGs Journal of Current Studies in SDGs Journal of Law and Bibliometrics Studies Open Access DRIVERset Journal of Innovative Technology and Sustainability Education
Riski Ramadani
Universitas Negeri Surabaya
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Multiple Intelligences in Digital Physics Learning for Education for Sustainable Development Hanan Zaki Alhusni; Titin Sunarti; Hanandita Veda Saphira; Riski Ramadani
Journal of Current Studies in SDGs Vol. 1 No. 4 (2025): December
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jocsis.1.4.101

Abstract

Objective: This study aims to synthesise research on the application of Multiple Intelligences (MI) in digital physics learning within the framework of Education for Sustainable Development (ESD). The goal is to map trends, highlight opportunities for personalised, sustainability-oriented learning, and identify gaps that hinder the integration of MI and digital technologies to foster sustainability competencies. Method: A Systematic Literature Review (SLR) was conducted following the PRISMA 2020 guidelines. Articles were collected from Google Scholar, Scopus, IEEE Xplore, ERIC, and ScienceDirect, limited to peer-reviewed studies published between 2018 and 2023 in English or Indonesian. Forty eligible studies were analysed thematically and through content analysis. Results: The findings show that MI-based digital learning enhances students' motivation, engagement, conceptual understanding, and academic performance. Interactive simulations, video-based modules, virtual experiments, and AR/VR applications offer personalised learning aligned with students' dominant intelligences. MI also supports ESD competencies such as critical thinking, collaboration, and sustainability awareness, though aspects like environmental literacy, social responsibility, and ethical reasoning remain underexplored. Novelty: This review uniquely links the MI, physics education, and ESD domains, which are rarely integrated in prior studies. It emphasises MI's potential to enhance cognitive outcomes while embedding sustainability values into physics education. A conceptual roadmap is proposed to align MI-based digital physics learning with the Sustainable Development Goals.
Multiple Intelligences in Digital Physics Learning for Education for Sustainable Development Hanan Zaki Alhusni; Titin Sunarti; Hanandita Veda Saphira; Riski Ramadani
Journal of Current Studies in SDGs Vol. 1 No. 4 (2025): December
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jocsis.1.4.101

Abstract

Objective: This study aims to synthesise research on the application of Multiple Intelligences (MI) in digital physics learning within the framework of Education for Sustainable Development (ESD). The goal is to map trends, highlight opportunities for personalised, sustainability-oriented learning, and identify gaps that hinder the integration of MI and digital technologies to foster sustainability competencies. Method: A Systematic Literature Review (SLR) was conducted following the PRISMA 2020 guidelines. Articles were collected from Google Scholar, Scopus, IEEE Xplore, ERIC, and ScienceDirect, limited to peer-reviewed studies published between 2018 and 2023 in English or Indonesian. Forty eligible studies were analysed thematically and through content analysis. Results: The findings show that MI-based digital learning enhances students' motivation, engagement, conceptual understanding, and academic performance. Interactive simulations, video-based modules, virtual experiments, and AR/VR applications offer personalised learning aligned with students' dominant intelligences. MI also supports ESD competencies such as critical thinking, collaboration, and sustainability awareness, though aspects like environmental literacy, social responsibility, and ethical reasoning remain underexplored. Novelty: This review uniquely links the MI, physics education, and ESD domains, which are rarely integrated in prior studies. It emphasises MI's potential to enhance cognitive outcomes while embedding sustainability values into physics education. A conceptual roadmap is proposed to align MI-based digital physics learning with the Sustainable Development Goals.
Integrating Earthquake Technologies into Physics Learning for Education for Sustainable Development: A Systematic Literature Review Hanan Zaki Alhusni; Riski Ramadani; Binar Kurnia Prahani; Titin Sunarti; Madlazim Madlazim; Muhammad Rey Dafa Ahmadi
Journal of Innovative Technology and Sustainability Education Vol. 1 No. 2 (2025): August
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jitse.1.2.86

Abstract

Objective: This study aims to synthesize current research on integrating earthquake-related technologies into physics education within the framework of Education for Sustainable Development (ESD). The objective is to examine how these technologies contribute to students' scientific literacy, critical thinking, and disaster preparedness, while also aligning with sustainability goals such as SDG 4 (Quality Education) and SDG 11 (Sustainable Cities and Communities). Method: A Systematic Literature Review (SLR) was conducted using the PRISMA 2020 framework. A total of 546 records were identified from databases, including Scopus, Web of Science, ERIC, and ScienceDirect, with 38 studies meeting the inclusion criteria after screening. Data were analyzed thematically and categorized into technological approaches, pedagogical strategies, and reported learning outcomes. Results: The findings demonstrate that earthquake technologies, including VR/AR simulations, shake tables, and real-time sensors, have a positive impact on student engagement, conceptual understanding, and disaster risk awareness. Pedagogical integration through inquiry-based, project-based, gamification, and problem-solving approaches enhances collaboration, critical thinking, and contextual application of physics concepts. However, challenges remain in terms of limited access to technology, insufficient teacher training, and the lack of longitudinal evidence. Novelty: Unlike previous studies that treated disaster education and physics pedagogy separately, this review bridges both domains under the ESD agenda. It highlights the transformative role of physics classrooms as laboratories for resilience and sustainability, providing a comprehensive framework for integrating disaster-related technologies into science education.
Trends and Mapping of Research on Artificial Intelligence-Based Antenna Optimisation: A Bibliometric Analysis Riski Ramadani; Afiyah Nikmah; Nisaul Fadhilah; Rohim Aminullah Firdaus; Noer Risky Ramadhani
Journal of Law and Bibliometrics Studies Vol. 1 No. 2 (2025): August
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jolabis.1.2.85

Abstract

Objective: This study aims to map the global research landscape on artificial intelligence (AI)-based antenna optimisation using a bibliometric approach. The objective is to identify publication trends, key contributors, collaborative networks, and emerging themes that define the development of this research domain. Method: The analysis was based on 4,814 documents retrieved from the Scopus database for the period 2010–2025. Data preprocessing included deduplication and keyword harmonisation. Bibliometric analysis was conducted using performance metrics (publication trends, influential authors, journals, countries) and science mapping (co-authorship, co-occurrence, co-citation) with VOSviewer and Bibliometrix. Results: Findings reveal three distinct publication phases: initial stagnation (2010–2016), growth (2017–2019), and exponential expansion (2020–2024), with a peak in 2023. China dominates global research output, followed by the United States and India. IEEE journals, particularly IEEE Access and IEEE Transactions on Antennas and Propagation, serve as the primary publication platforms. Co-authorship analysis indicates a highly centralised collaboration network with hubs like Zhang and Wang. At the same time, thematic mapping shows a strong focus on machine learning, deep learning, 5G or 6G technologies, and adaptive antenna design. Novelty: This paper provides a systematic, data-driven overview of the intellectual structure and thematic evolution of AI-based antenna optimisation research. It identifies gaps such as limited experimental validation, standardisation issues, and the need for AI-driven inverse design methods for next-generation communication systems.
Artificial Intelligence in Physics Learning for Education for Sustainable Development: A Bibliometric Analysis Riski Ramadani; Hanan Zaki Alhusni; Titin Sunarti; Madlazim Madlazim
Journal of Law and Bibliometrics Studies Vol. 1 No. 3 (2025): December
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jolabis.1.3.95

Abstract

Objective: This study aims to map the global research landscape on Artificial Intelligence (AI) in physics education within the framework of Education for Sustainable Development (ESD) using a bibliometric approach. The objective is to identify publication trends, key contributors, collaborative networks, and emerging themes that define the development of this research domain. Method: The analysis was based on 4,814 documents retrieved from the Scopus database for the period 2015–2025. Data preprocessing included deduplication and keyword harmonization. Bibliometric analysis was conducted using performance indicators (publication output, influential authors, journals, countries, institutions) and science mapping (co-authorship, co-occurrence, co-citation) with VOSviewer and Bibliometrix. Results: Findings reveal three phases of publication dynamics: initial emergence (2015–2018), growth (2019–2021), and accelerated expansion (2022–2024), with a peak in 2024. The United States dominates global output, followed by China and Indonesia. Physics-focused journals such as Physical Review Physics Education Research and Journal of Physics: Conference Series serve as major outlets. Co-authorship networks show a core cluster in Europe and North America, while Asian and Global South researchers are increasingly active. Thematic mapping highlights clusters on AI-enabled assessment, machine learning, Large Language Models (LLMs), and sustainability-oriented physics education. Novelty: This paper provides a systematic overview of the intellectual structure and thematic evolution of AI-based physics education for ESD. It identifies gaps, including limited cross-country collaboration, low experimental validation, and uneven global participation, while highlighting opportunities for ethical, inclusive, and sustainability-aligned AI integration in future physics learning.
Mapping the Global Research Landscape of Problem-Based Learning in Digital Learning Environments: A Bibliometric Analysis Toward Achieving SDG 4 Hanan Zaki Alhusni; Binar Kurnia Prahani; Budi Jatmiko; Riski Ramadani; Noer Risky Ramadhani; Lindsay Natalia Bergsma; Abd. Hadi Bunyamin
Journal of Law and Bibliometrics Studies Vol. 2 No. 2 (2026): August
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jolabis.2.2.137

Abstract

Objective: The study aims to map the global research landscape of Problem-Based Learning (PBL) in Digital Learning Environments (DLE) using a bibliometric approach. The objective is to identify publication trends, major contributors, collaboration patterns, and emerging research themes supporting the development of sustainable digital education aligned with Sustainable Development Goal 4 (SDG 4). Method: The analysis was conducted on 2,134 documents retrieved from the Scopus database covering publications up to 2025. Data preprocessing involved duplicate removal, document filtering, and keyword harmonization. Bibliometric analysis employed performance indicators (annual publications, productive authors, sources, affiliations, and countries) and science mapping techniques (co-authorship, keyword co-occurrence, and citation analysis) using Bibliometrix and VOSviewer to visualize the intellectual structure of the field. Results: The findings reveal a substantial growth of research in this field, particularly following the global acceleration of digital education. China and the United States dominate research productivity, followed by emerging contributions from countries such as Indonesia. Publication sources are largely dominated by conference proceedings and journals in educational technology and computer science, highlighting the field's interdisciplinary nature.  Novelty: This study provides a comprehensive mapping of the intellectual structure and thematic evolution of PBL research in Digital Learning Environments. It identifies research gaps, including limited international collaboration and the need for greater integration of emerging technologies such as artificial intelligence. The findings offer directions for future research to strengthen sustainable digital learning innovation and support the achievement of SDG 4.
Trends and Mapping of Research on Artificial Intelligence-Based Antenna Optimisation: A Bibliometric Analysis Riski Ramadani; Afiyah Nikmah; Nisaul Fadhilah; Rohim Aminullah Firdaus; Noer Risky Ramadhani
Journal of Law and Bibliometrics Studies Vol. 1 No. 2 (2025): August
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jolabis.1.2.85

Abstract

Objective: This study aims to map the global research landscape on artificial intelligence (AI)-based antenna optimisation using a bibliometric approach. The objective is to identify publication trends, key contributors, collaborative networks, and emerging themes that define the development of this research domain. Method: The analysis was based on 4,814 documents retrieved from the Scopus database for the period 2010–2025. Data preprocessing included deduplication and keyword harmonisation. Bibliometric analysis was conducted using performance metrics (publication trends, influential authors, journals, countries) and science mapping (co-authorship, co-occurrence, co-citation) with VOSviewer and Bibliometrix. Results: Findings reveal three distinct publication phases: initial stagnation (2010–2016), growth (2017–2019), and exponential expansion (2020–2024), with a peak in 2023. China dominates global research output, followed by the United States and India. IEEE journals, particularly IEEE Access and IEEE Transactions on Antennas and Propagation, serve as the primary publication platforms. Co-authorship analysis indicates a highly centralised collaboration network with hubs like Zhang and Wang. At the same time, thematic mapping shows a strong focus on machine learning, deep learning, 5G or 6G technologies, and adaptive antenna design. Novelty: This paper provides a systematic, data-driven overview of the intellectual structure and thematic evolution of AI-based antenna optimisation research. It identifies gaps such as limited experimental validation, standardisation issues, and the need for AI-driven inverse design methods for next-generation communication systems.
Artificial Intelligence in Physics Learning for Education for Sustainable Development: A Bibliometric Analysis Riski Ramadani; Hanan Zaki Alhusni; Titin Sunarti; Madlazim Madlazim
Journal of Law and Bibliometrics Studies Vol. 1 No. 3 (2025): December
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jolabis.1.3.95

Abstract

Objective: This study aims to map the global research landscape on Artificial Intelligence (AI) in physics education within the framework of Education for Sustainable Development (ESD) using a bibliometric approach. The objective is to identify publication trends, key contributors, collaborative networks, and emerging themes that define the development of this research domain. Method: The analysis was based on 4,814 documents retrieved from the Scopus database for the period 2015–2025. Data preprocessing included deduplication and keyword harmonization. Bibliometric analysis was conducted using performance indicators (publication output, influential authors, journals, countries, institutions) and science mapping (co-authorship, co-occurrence, co-citation) with VOSviewer and Bibliometrix. Results: Findings reveal three phases of publication dynamics: initial emergence (2015–2018), growth (2019–2021), and accelerated expansion (2022–2024), with a peak in 2024. The United States dominates global output, followed by China and Indonesia. Physics-focused journals such as Physical Review Physics Education Research and Journal of Physics: Conference Series serve as major outlets. Co-authorship networks show a core cluster in Europe and North America, while Asian and Global South researchers are increasingly active. Thematic mapping highlights clusters on AI-enabled assessment, machine learning, Large Language Models (LLMs), and sustainability-oriented physics education. Novelty: This paper provides a systematic overview of the intellectual structure and thematic evolution of AI-based physics education for ESD. It identifies gaps, including limited cross-country collaboration, low experimental validation, and uneven global participation, while highlighting opportunities for ethical, inclusive, and sustainability-aligned AI integration in future physics learning.
Mapping the Global Research Landscape of Problem-Based Learning in Digital Learning Environments: A Bibliometric Analysis Toward Achieving SDG 4 Hanan Zaki Alhusni; Binar Kurnia Prahani; Budi Jatmiko; Riski Ramadani; Noer Risky Ramadhani; Lindsay Natalia Bergsma; Abd. Hadi Bunyamin
Journal of Law and Bibliometrics Studies Vol. 2 No. 2 (2026): August
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jolabis.2.2.137

Abstract

Objective: The study aims to map the global research landscape of Problem-Based Learning (PBL) in Digital Learning Environments (DLE) using a bibliometric approach. The objective is to identify publication trends, major contributors, collaboration patterns, and emerging research themes supporting the development of sustainable digital education aligned with Sustainable Development Goal 4 (SDG 4). Method: The analysis was conducted on 2,134 documents retrieved from the Scopus database covering publications up to 2025. Data preprocessing involved duplicate removal, document filtering, and keyword harmonization. Bibliometric analysis employed performance indicators (annual publications, productive authors, sources, affiliations, and countries) and science mapping techniques (co-authorship, keyword co-occurrence, and citation analysis) using Bibliometrix and VOSviewer to visualize the intellectual structure of the field. Results: The findings reveal a substantial growth of research in this field, particularly following the global acceleration of digital education. China and the United States dominate research productivity, followed by emerging contributions from countries such as Indonesia. Publication sources are largely dominated by conference proceedings and journals in educational technology and computer science, highlighting the field's interdisciplinary nature.  Novelty: This study provides a comprehensive mapping of the intellectual structure and thematic evolution of PBL research in Digital Learning Environments. It identifies research gaps, including limited international collaboration and the need for greater integration of emerging technologies such as artificial intelligence. The findings offer directions for future research to strengthen sustainable digital learning innovation and support the achievement of SDG 4.
Analisis Pengaruh Variasi Fiber Doped Amplifier dan Panjang Gelombang Laser terhadap Optical Power pada Perancangan Sistem FMCW LiDAR: Analysis of the Effect of Variations in Doped Fiber Amplifier and Laser Wavelength on Optical Power in FMCW LiDAR System Design Riski Ramadani; Meta Yantidewi; Rohim Aminullah Firdaus; Afiyah Nikmah
Jurnal Kolaboratif Sains Vol. 7 No. 5: MEI 2024 - Jurnal Kolaboratif Sains (JKS)
Publisher : Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/jks.v7i5.5267

Abstract

Frequency Modulated Continuous Wave (FMCW) LiDAR merupakan teknologi pendeteksian objek dengan teknik memodulasi frekuensi sinar laser secara kontinu. FMCW LiDAR memiliki kelebihan dalam mendeteksi objek karena dapat menghasilkan pendeteksian objek secara akurat. Salah satu paramater yang berperan dalam pendeteksian sistem ini adalah optical power. Namun optical power dapat berkurang karena ketidaksesauian kombinasi fiber doped amplifier dengan panjang gelombang laser sehingga pada penelitian ini dilakukan pengukuran optical power secara simulasi terhadap berbagai jenis fiber doped amplifier dan panjang gelombang laser. Hasil penelitian menunjukan bahwa jenis Holmium Doped Fiber Amplifier (HDFA) mengeluarkan optical power yang lebih besar dibandingkan jenis fiber doped amplifier lainnya, yakni sebesar 20,02 mW. Selain itu, panjang gelombang 1550 nm menghasilkan keluaran optical power yang optimal diberbagai jenis fiber doped amplifier. Pada penelitian ini semua jenis fiber doped amplifier dan panjang gelombang laser menghasilkan frekuensi beat sebesar 20 MHz dan objek terdeteksi pada jarak 100 meter.
Co-Authors Abd. Hadi Bunyamin Afiyah Nikmah Binar Kurnia Prahani Budi Jatmiko Hanan Zaki Alhusni Hanandita Veda Saphira Lindsay Natalia Bergsma Madlazim Madlazim Muhammad Rey Dafa Ahmadi Nisaul Fadhilah Noer Risky Ramadhani Noer Risky Ramadhani ROHIM AMINULLAH FIRDAUS TITIN SUNARTI Yantidewi, Meta