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INDONESIAN ELEMENTARY SCHOOLS TEACHERS™ ATTITUDE TOWARDS VIDEO CONFERENCING PLATFORM IMPLEMENTATION DURING COVID-19 PANDEMIC Machmud, Muhammad Takwin; Ramadhani, Noer Risky; Sipahutar, Rini Juliani; Manjani, Nurhudayah; Silalahi, Natalia; Damayanti, Nina Afria; Syahrial, Syahrial; Bangun, Melly Br
SCHOOL EDUCATION JOURNAL PGSD FIP UNIMED Vol. 12 No. 4 (2022): SCHOOL EDUCATION JOURNAL PGSD FIP UNIMED
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/sejpgsd.v12i4.40420

This study is identifying elementary schools teacher attitudes towards video conferencing platform implementation during Covid-19 pandemic. The research aims include (1) to identify teachers™ attitude towards implementing video conferencing platforms for learning (2) to identify teachers' challenges encountered during implementing video conferencing and how to overcome that challenge. The 103 elementary schools teachers were included. The teacher selected by simple random sampling techniques. The questionnaire's content is based on teachers' attitudes toward using video conferencing in the classroom during the COVID-19 epidemic, as measured by the following indicators: efficiency, effectiveness, motivation, and variety of obstacles. The elementary schools teachers™ attitude shows positive responses to video conferencing in learning such as providing various learning activities, providing flexibility in teaching process, easiness to access learning materials, and ease in assessing and monitoring students' learning progress. Furthermore, the result reveals the majority of the elementary schools teachers faced technical issues and availability as obstacles in implementing a video conferencing platform. The majority of elementary schools teachers were able to resolve these technological difficulties by exploring other teaching strategies and seeking professional advice.

Trends and Mapping of Research on Artificial Intelligence-Based Antenna Optimisation: A Bibliometric Analysis Ramadani, Riski; Nikmah, Afiyah; Fadhilah, Nisaul; Firdaus , Rohim Aminullah; Ramadhani, Noer Risky
Journal of Law and Bibliometrics Studies Vol. 1 No. 2 (2025): July
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

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.

Trends and Mapping of Research on Artificial Intelligence-Based Antenna Optimisation: A Bibliometric Analysis Ramadani, Riski; Nikmah, Afiyah; Fadhilah, Nisaul; Firdaus , Rohim Aminullah; Ramadhani, Noer Risky
Journal of Law and Bibliometrics Studies Vol. 1 No. 2 (2025): July
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

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.

Profile of E-STATPHYS Assisted PBL Model on Static Fluid Material to Improve Problem-Solving Skills of High School Students Hareni, Siska Agustin Sha; Prahani, Binar Kurnia; Irani, Dhea Wanda; Lutfiani, Elvia Reza; Muawiyah, Nurul; Hidayatin, Nofri; Ramadhani, Noer Risky
Journal of Innovative Technology and Sustainability Education Vol. 2 No. 1 (2026): APRIL
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jitse.2.1.125

Objective: This study aims to analyze the problem-solving skills of high school students as a basis for considering the application of the Problem Based Learning (PBL) model assisted by the E-STATPHYS digital book on static fluid material. Method: This study used a qualitative descriptive method with 105 grade XI students at SMA Negeri 1 Kedungpring as subjects. Data collection techniques included a preliminary survey in the form of a problem-solving skills test, student response questionnaires, and interviews with physics teachers. Data were analyzed to identify the level of students problem-solving skills. Results: The results showed that 98 students were in the low problem-solving skills category, 7 students were in the medium category, and there were no students in the high category. These findings indicate that students problem-solving skills on static fluid material still need to be significantly improved. Novelty: The novelty of this study lies in the use of the results of the initial analysis of problem-solving skills as a basis for the development and application of the Problem Based Learning model assisted by the E-STATPHYS digital book, which is specifically designed to support physics learning on static fluid material and facilitate the improvement of students problem-solving skills.

Design Optimization of Rectangular Microstrip Antenna Using Deep Neural Network for 3 GHz Applications in Support of SDG 9 Ramadani, Riski; Nikmah, Afiyah; Rachmawati, Arum Vonie; Firdaus, Rohim Aminullah Firdaus; Ramadhani, Noer Risky
Journal of Current Studies in SDGs Vol. 2 No. 1 (2026): March
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jocsis.2.1.130

Objective: This study aims to investigate the effectiveness of Deep Neural Networks (DNN) for optimizing the design of a rectangular microstrip antenna operating at a target frequency of 3 GHz. The research focuses on improving antenna design efficiency by predicting antenna performance parameters based on geometric characteristics. Method: The study employed a computational simulation approach combined with machine learning techniques. A synthetic dataset consisting of 6000 antenna configurations was generated using analytical microstrip antenna equations. The dataset included geometric parameters such as dielectric constant, substrate thickness, patch width, patch length, and inset feed position. A Deep Neural Network model was trained to predict resonant frequency, return loss, and input impedance. The trained model was then used as a surrogate model to evaluate 30,000 candidate antenna designs and identify the optimal configuration. Result: The proposed model achieved high predictive accuracy with values of 0.9987 for resonant frequency prediction and 0.9988 for input impedance prediction. The optimized antenna design produced a resonant frequency of 2.996 GHz, return loss of −18.70 dB, and input impedance of 53.95 Ω, which closely match the target specifications for S-band wireless applications. Novelty: The study demonstrates that Deep Neural Networks can significantly accelerate antenna design optimization by replacing repetitive electromagnetic simulations with data-driven prediction models.

Effectiveness of Learning With PBL Model Based on E-Modules to Improve Critical Thinking Skills Novianti, Aulia Betha; Jatmiko, Budi; Prahani, Binar Kurnia; Ramadhani, Noer Risky
Journal of Digitalization in Physics Education Vol. 1 No. 3 (2025): December
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jdpe.v1i3.42451

Objective: This study aims to examine the effectiveness of physics e-modules based on the Problem-Based Learning (PBL) model in improving students’ critical thinking skills on static fluid concepts. The focus is to evaluate the implementation of learning, measure the improvement of students’ critical thinking ability, and analyze student responses after applying the PBL-based e-modules. Method: The research employed a proper experimental design with a pre-test and post-test control group, conducted at MA Ma’arif Bangil, Pasuruan, Indonesia. A total sampling technique was used, with class XA as the experimental group and class XB as the control group. Data were collected using observation sheets, pre-test and post-test instruments, and student response questionnaires. Data analysis included N-Gain scores, normality and homogeneity tests, t-tests, and descriptive analysis for student responses. Results: The findings showed that the implementation of PBL-based e-modules reached an average of 91.8% categorized as very good. Students in the experimental class demonstrated a significant improvement in critical thinking skills, with an average N-Gain of 0.512 (moderate), compared to 0.212 (low) in the control group. Furthermore, student responses were predominantly in the “good” and “very good” categories, indicating positive perceptions of the learning approach. Novelty: This study highlights the integration of PBL with interactive e-modules as an innovative learning strategy that not only enhances students’ critical thinking skills but also addresses the limitations of conventional print modules. It provides empirical evidence that digital-based problem-oriented instruction is highly relevant to fostering 21st-century competencies in science learning.

Development of Parabolic Motion Learning Devices Based on Technology-Enhanced Guided Inquiry with a Sport Education Approach to Improve High School Students' Critical Thinking Skills Astutik, Widi; Wasis, Wasis; Jatmiko, Budi; Ramadhani, Noer Risky
Journal of Digitalization in Physics Education Vol. 2 No. 1 (2026): April
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jdpe.v2i1.52270

Objective: This study aims to develop a parabolic motion learning tool based on a guided inquiry model with a sports education approach to improve the critical thinking skills of high school students. Method: This research is a research and development (R&D) study using the ADDIE model, which includes analysis, design, development, implementation, and evaluation. The subjects consisted of 11th-grade high school students involved in both limited and extensive trials. The research instruments included a tool validation sheet, a learning implementation observation sheet, a student response questionnaire, and a critical thinking skills test. Data analysis was conducted using validity, reliability, N-gain, normality, homogeneity, paired t-test, and ANOVA. Results: The results showed that the developed learning tool met the criteria for highly valid with a percentage between 84% and 98%; practical based on the learning implementation category (very good) and student response (87.88%), and effective based on the increase in the N-gain value in the moderate category (0.59–0.62). The statistical test results also showed a significant increase between pretest and posttest scores, and no significant differences between classes, demonstrating the consistent effectiveness of the learning tools. Novelty: The novelty of this research lies in the integration of a guided inquiry model with a sports education approach in physics instruction on parabolic motion to train critical thinking skills through contextual learning based on sports activities, a practice that has not been widely explored in previous research.

Design Optimization of Rectangular Microstrip Antenna Using Deep Neural Network for 3 GHz Applications in Support of SDG 9 Ramadani, Riski; Nikmah, Afiyah; Rachmawati, Arum Vonie; Firdaus, Rohim Aminullah Firdaus; Ramadhani, Noer Risky
Journal of Current Studies in SDGs Vol. 2 No. 1 (2026): March
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jocsis.2.1.130

Objective: This study aims to investigate the effectiveness of Deep Neural Networks (DNN) for optimizing the design of a rectangular microstrip antenna operating at a target frequency of 3 GHz. The research focuses on improving antenna design efficiency by predicting antenna performance parameters based on geometric characteristics. Method: The study employed a computational simulation approach combined with machine learning techniques. A synthetic dataset consisting of 6000 antenna configurations was generated using analytical microstrip antenna equations. The dataset included geometric parameters such as dielectric constant, substrate thickness, patch width, patch length, and inset feed position. A Deep Neural Network model was trained to predict resonant frequency, return loss, and input impedance. The trained model was then used as a surrogate model to evaluate 30,000 candidate antenna designs and identify the optimal configuration. Result: The proposed model achieved high predictive accuracy with values of 0.9987 for resonant frequency prediction and 0.9988 for input impedance prediction. The optimized antenna design produced a resonant frequency of 2.996 GHz, return loss of −18.70 dB, and input impedance of 53.95 Ω, which closely match the target specifications for S-band wireless applications. Novelty: The study demonstrates that Deep Neural Networks can significantly accelerate antenna design optimization by replacing repetitive electromagnetic simulations with data-driven prediction models.

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