Article Per Year (5 Year)
p-Index From 2020 - 2025
1.955
P-Index
This Author published in this journals
All Journal Al-Hijr: Journal of Adulearn World Journal International of Lingua and Technology World Psychology International Journal of Educational Narratives Journal of World Future Medicine, Health and Nursing Journal of Computer Science Advancements Journal of Moeslim Research Technik Journal of Selvicoltura Asean Research Psychologie, Orientation et Conseil Techno Agriculturae Studium of Research Research of Scientia Naturalis
Nizam, Zain
Unknown Affiliation
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Medicine & Pharmacology Nursing Physics Public Health Social Sciences Veterinary Other

Published : 14 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 14 Documents
Search

 1   2 
The Role of Project-Based Learning in Developing 21st Century Skills Silitubun, Evaristus; Costa, Bruna; Nizam, Zain
International Journal of Educational Narratives Vol. 2 No. 6 (2024)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/ijen.v2i6.1689

Abstract

Background: In recent years, the need for 21st-century skills such as critical thinking, collaboration, and creativity has become increasingly significant. Traditional education models often fall short in developing these competencies, making innovative teaching methods like Project-Based Learning (PBL) an important focus in modern educational research. PBL, with its emphasis on real-world problems and student-centered learning, has been seen as a promising approach to cultivate these essential skills. Objectives: This study aims to investigate the role of Project-Based Learning (PBL) in fostering the development of 21st-century skills among students. Method: A mixed-method approach was employed, utilizing both qualitative and quantitative data. Surveys and interviews were conducted with students and educators from various educational institutions that implemented PBL strategies in their curricula. The collected data were analyzed to identify the impacts of PBL on students’ skill development. Results: The findings revealed that PBL significantly contributes to the enhancement of key 21st-century skills. Students demonstrated improved problem-solving abilities, teamwork, communication, and creativity. Moreover, educators observed an increase in student engagement and motivation. Conclusion: Project-Based Learning is an effective pedagogical approach in fostering 21st-century skills. Its emphasis on real-world problem solving and collaborative work provides students with the necessary tools to thrive in an increasingly complex and dynamic world.
The Future of Medical Technology: Recent Innovations in Artificial Intelligence and Robotics for More Precise and Efficient Treatment Farah, Rina; Nizam, Zain
Journal of World Future Medicine, Health and Nursing Vol. 3 No. 2 (2025)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v3i2.1896

Abstract

The rapid advancement of artificial intelligence (AI) and robotics has transformed the landscape of medical technology, offering unprecedented precision, efficiency, and personalization in patient care. The integration of AI-driven diagnostics and robotic-assisted surgery has improved clinical decision-making, minimized human errors, and enhanced surgical outcomes. This study aims to explore recent innovations in AI and robotics in the medical field, assess their effectiveness in improving treatment precision, and identify challenges in their widespread adoption. A systematic review methodology was employed, analyzing recent peer-reviewed articles, case studies, and reports from medical institutions and technology developers. The findings indicate that AI-powered diagnostic tools significantly enhance early disease detection, while robotic surgery enables minimally invasive procedures with improved accuracy and reduced recovery times. However, challenges such as ethical concerns, high implementation costs, and regulatory hurdles remain key barriers to full-scale adoption. This study concludes that AI and robotics will play an increasingly vital role in modern medicine, revolutionizing healthcare delivery. Further research should focus on optimizing AI algorithms, addressing ethical considerations, and developing cost-effective solutions to ensure broader accessibility and acceptance in medical practice.
The Influence of Principal Transformational Leadership on Teacher Performance Nizam, Zain; Rahman, Rashid; Wei, Sun
International Journal of Educational Narratives Vol. 3 No. 2 (2025)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/ijen.v3i2.2154

Abstract

Background. Service learning has gained recognition as a valuable pedagogical approach in higher education, aiming to bridge the gap between academic theory and real-world practice. In the context of educational institutions, the role of leadership, particularly transformational leadership, plays a significant role in shaping the effectiveness of such programs. Purpose. This research explores the influence of principal transformational leadership on teacher performance within the framework of service learning in higher education institutions. Method. The study aims to assess how transformational leadership behaviors of school principals impact the engagement and performance of teachers involved in service learning programs. Using a quantitative research design, this study surveyed 150 teachers across several higher education institutions that implement service learning programs. Data were collected through questionnaires that assessed principals’ leadership styles and teachers’ performance in service learning contexts. Results. The results indicate that transformational leadership has a positive and significant effect on teacher performance, particularly in areas related to motivation, professional development, and commitment to service learning objectives. Teachers reported higher levels of engagement and effectiveness when their principals exhibited transformational leadership behaviors, such as inspirational motivation, individualized consideration, and intellectual stimulation. Conclusion. This study concludes that principals who embrace transformational leadership can significantly enhance teacher performance, thereby strengthening the impact of service learning programs.  
Building Police Mental Resilience in 2025: The Role of Self-Efficacy and Perceived Organizational Support in Strengthening the Resilience of Samapta Directorate Members Fitri, Aroviani Amsa; Kusmaryani, Rosita Endang; Rosul, Ahmad; Nizam, Zain
World Psychology Vol. 4 No. 1 (2025)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/wp.v4i1.877

Abstract

Working as a police officer requires readiness to face the risk of danger and heavy workload, high pressure when facing threats and uncertain situations. This study was motivated by the phenomenon of the discovery of a low level of resilience of police members. Self-efficacy and perceived organizational support are assumed to be supporting factors in the formation of resilience of police members of the Samapta Directorate. This study aims to examine the role of self-efficacy and perceived organizational support in increasing the resilience of police members of the Samapta Directorate of the DIY Regional Police. This study uses a quantitative method with an explanatory survey research type. The sample of this study used 122 members of the Samapta Directorate of the DIY Regional Police who were selected using the proportionate stratified random sampling technique. Resilience was measured using the CD-RISC 10 scale, self-efficacy is measured by the GSE scale and POS is measured by the SPOS scale. Hypothesis testing using multiple regression analysis with the help of JASP 19.3 program. The results of the study indicate that self-efficacy and perceived organizational support have a significant effect on resilience and are proven to be factors in forming the resilience of members of the Samapta Directorate. 
Personalized Learning through ChatGPT: A Quasi-Experimental Study on Adaptive Curriculum in High School Settings Muhammad, Muhammad; Nizam, Zain; Razak, Faisal
Al-Hijr: Journal of Adulearn World Vol. 4 No. 2 (2025)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/alhijr.v4i2.982

Abstract

The challenge of catering to diverse learning paces and styles in traditional high school classrooms often limits student potential. The emergence of advanced AI, such as ChatGPT, presents a novel opportunity to create adaptive learning environments that personalize educational content in real-time. This study aimed to investigate the effectiveness of a ChatGPT-driven adaptive curriculum on student academic performance and engagement compared to conventional, non-adaptive teaching methods. A quasi-experimental, pre-test/post-test design was conducted with 110 high school students. The intervention group (n=55) utilized an adaptive curriculum where content was dynamically adjusted by ChatGPT based on performance, while the control group (n=55) received standard instruction. Academic performance was measured via subject-specific tests, and engagement was assessed using the Student Engagement Instrument (SEI). The intervention group demonstrated a statistically significant improvement in academic performance (p < .01) and higher engagement scores (p < .05) compared to the control group. The adaptive curriculum effectively addressed individual learning gaps and maintained student interest. Integrating ChatGPT to facilitate personalized, adaptive curricula is a highly effective strategy for enhancing both academic achievement and student engagement in high school settings. This approach offers a scalable solution to individualized instruction.
The Influence of Natural Language-Based Chatbot Usage on User Experience in Online Customer Service Jumriyah, Jumriyah; Nizam, Zain; Idris, Haziq
Journal International of Lingua and Technology Vol. 4 No. 1 (2025)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/jiltech.v4i1.821

Abstract

The rapid development of artificial intelligence has led to an increased use of natural language-based chatbots in various industries, particularly in online customer service. These chatbots have become essential tools for improving customer engagement, providing timely support, and enhancing the overall user experience. However, despite their growing popularity, the impact of chatbot usage on user experience in online customer service remains underexplored. This study investigates the influence of natural language-based chatbot usage on user experience in online customer service settings. The research aims to evaluate how chatbot interactions affect customer satisfaction, ease of use, and perceived efficiency in addressing customer queries. A mixed-methods approach was employed, utilizing quantitative surveys and qualitative interviews with users who interacted with a natural language-based chatbot on an e-commerce platform. The data collected were analyzed to assess the correlation between chatbot usage and user experience. The results revealed that users who interacted with the chatbot reported higher levels of satisfaction and perceived efficiency compared to those who used traditional customer service methods. The ease of use and quick response times contributed to positive user experiences, although some users expressed concerns about the chatbot’s ability to handle complex queries. The study concludes that natural language-based chatbots can significantly improve user experience in online customer service, but further improvements are needed to enhance their capabilities in addressing more complex issues.
Mobile Application Design Based on Natural Language Processing to Improve the Quality of Health Services Ridwan, Achmad; Nizam, Zain; Satybaldy, Daniyar
Journal of Computer Science Advancements Vol. 3 No. 1 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v3i1.1626

Abstract

The increasing demand for efficient and personalized health services has driven the integration of advanced technologies into healthcare systems. Mobile applications leveraging natural language processing (NLP) offer promising solutions to improve patient communication, diagnostic accuracy, and service delivery. Despite advancements, challenges remain in developing user-friendly applications that address diverse healthcare needs. This research focuses on designing a mobile application based on NLP to enhance the quality of health services, emphasizing usability, accuracy, and accessibility. The study employs a user-centered design approach combined with experimental evaluation. The application was developed using Python-based NLP libraries, integrating features such as symptom analysis, medical query responses, and appointment scheduling. A prototype was tested with 150 participants, including patients and healthcare professionals, to evaluate performance metrics such as response accuracy, user satisfaction, and system reliability. The findings indicate that the NLP-based application achieved an 85% accuracy rate in interpreting medical queries and a 90% user satisfaction rate. Participants reported improved communication with healthcare providers and faster access to relevant medical information. However, challenges such as handling complex medical terminology and ensuring data privacy were noted. The study concludes that NLP-powered mobile applications have significant potential to improve health service quality by enabling efficient and accurate communication between patients and providers. Addressing challenges related to data security and expanding linguistic capabilities will be essential for future development. The research underscores the importance of integrating advanced technologies to meet the evolving needs of the healthcare sector.
Robotic Arm Control System Design for High Precision Work Sinuraya, Enda Wista; Winardi, Bambang; Nizam, Zain
Journal of Moeslim Research Technik Vol. 2 No. 2 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v2i2.1928

Abstract

The demand for high-precision tasks in various industries, such as manufacturing and healthcare, necessitates the development of advanced robotic systems. Traditional robotic arms often struggle to meet the accuracy and repeatability required for precision work. This research focuses on designing a control system specifically tailored for robotic arms to enhance their performance in high-precision applications. The primary goal of this study is to develop an advanced control system for robotic arms that improves accuracy and reliability during precision tasks. The research aims to evaluate the effectiveness of various control algorithms in optimizing the performance of the robotic arm. A systematic approach was employed, utilizing simulation software to design and test different control strategies, including PID control and adaptive control methods. Performance metrics such as positional accuracy, response time, and stability were analyzed through a series of experiments conducted in both simulated and real-world environments. The implementation of the advanced control system resulted in significant improvements in the robotic arm's performance. The adaptive control method achieved a positional accuracy of 0.1 mm, with a response time reduction of 30% compared to traditional PID control. These findings demonstrate the effectiveness of the proposed control strategies in enhancing precision. The research successfully developed a robust control system for robotic arms, significantly improving their ability to perform high-precision tasks.
Machine Vision for Quality Control in Halal Food Production: A Deep Learning Approach A, Chevy Herli Sumerli; Farah, Rina; Nizam, Zain
Journal of Moeslim Research Technik Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v2i3.2351

Abstract

Ensuring the quality and integrity of halal food products has become increasingly important with the growth of the global halal food industry. Conventional quality control methods, which rely on manual inspection and laboratory testing, are often time-consuming, subjective, and prone to human error. This study aims to develop and evaluate a machine vision system powered by deep learning algorithms to automate quality control processes in halal food production. A convolutional neural network (CNN)-based framework was implemented to classify and detect defects, contamination, and non-halal elements in food products. The system was trained using a dataset of 12,500 labeled images collected from halal-certified production facilities, with data augmentation applied to improve model generalization. Performance metrics, including accuracy, precision, recall, and F1-score, were used to evaluate the system. The results demonstrate that the proposed deep learning model achieved 96.8% classification accuracy, with high precision (95.5%) and recall (97.2%), significantly outperforming conventional machine vision techniques. The findings indicate that deep learning-driven machine vision can provide fast, reliable, and scalable quality control, supporting compliance with halal standards while reducing operational costs. This research highlights the potential of artificial intelligence to modernize quality assurance systems in halal food industries.  
Biodiversity Conservation in the Anthropocene: Challenges and Solutions Fariq, Aiman; Nizam, Zain; Idris, Haziq
Journal of Selvicoltura Asean Vol. 1 No. 3 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsa.v1i3.1660

Abstract

The Anthropocene epoch is characterized by significant human impact on the Earth's ecosystems, leading to unprecedented biodiversity loss. Rapid urbanization, climate change, and habitat destruction pose severe challenges to conservation efforts. Understanding these challenges is critical for developing effective strategies to preserve biodiversity. This study aims to identify the key challenges to biodiversity conservation in the Anthropocene and propose actionable solutions. By examining current conservation practices and their limitations, the research seeks to highlight innovative approaches that can enhance biodiversity protection. A comprehensive literature review was conducted, analyzing case studies and existing conservation strategies across various ecosystems. The study employs qualitative and quantitative methods to assess the effectiveness of these strategies in addressing biodiversity loss. Findings indicate that habitat degradation, climate change, and invasive species are the primary threats to biodiversity. Successful conservation initiatives, such as community-based management and the establishment of protected areas, demonstrate potential pathways for enhancing biodiversity resilience. Additionally, integrating traditional ecological knowledge with scientific approaches has shown promise in improving conservation outcomes. This research underscores the urgent need for adaptive and collaborative conservation strategies in the Anthropocene. By addressing the identified challenges and implementing proposed solutions, stakeholders can work towards more effective biodiversity conservation, ensuring the protection of ecosystems for future generations.
Co-Authors A, Chevy Herli Sumerli Achmad Ridwan, Achmad Anis, Nina Bambang Winardi Belangi, Siska Putri Busnawir Busnawir Chai, Nong Costa, Bruna Enda Wista Sinuraya Farah, Rina Fariq, Aiman Fitri, Aroviani Amsa Idris, Haziq Jumriyah, Jumriyah Liz Yanti Andriyani Muhammad Hazmi Muhammad Muhammad Nurul Huda Rahim, Syaifullah Rahman, Rashid Razak, Faisal Rosita Endang Kusmaryani Rosul, Ahmad Satybaldy, Daniyar Silitubun, Evaristus Siti Aisyah Sun Wei