Journal of Education and Technology Development

The Role of Agricurtural Technology in Achieving Sustainable Food Security

Yudi Garnida — 2026-03-05

Sustainable food security is a critical challenge facing the agricultural sector amidst population growth, climate change, and limited natural resources. Agricultural technology presents a strategic solution to increase the productivity, efficiency, and sustainability of agricultural systems. This study aims to analyze the role of agricultural technology in achieving sustainable food security and identify various barriers to its implementation. The research method used was qualitative with a descriptive approach, utilizing secondary data obtained through literature review of relevant scientific journals, books, and research reports. The results indicate that agricultural technology plays a crucial role in increasing productivity and efficiency through precision agriculture, assisting adaptation to climate change through superior varieties, supporting modern, land-saving agriculture such as hydroponics and aeroponics, reducing yield losses through storage and drying technologies, and supporting environmentally friendly agriculture through the use of biopesticides and organic fertilizers. However, the implementation of agricultural technology still faces various obstacles, such as limited capital and infrastructure, low quality human resources, and social and institutional constraints. Therefore, support from the government and relevant parties through the provision of facilities, training, and mentoring is needed to increase the adoption of agricultural technology. With optimal technology implementation, sustainable food security can be achieved more effectively.

Educational Management Strategies in Improving Student Discipline at Special Needs Schools in Batam City

Aprizal Yusril — 2026-05-18

This study aims to analyze educational management strategies in improving student discipline at special needs schools in Batam City. Student discipline is an important aspect of the educational process, particularly in special education settings where students possess diverse cognitive, emotional, physical, and behavioral characteristics. This research employed a qualitative descriptive approach to obtain an in-depth understanding of how educational management strategies are implemented in improving discipline among students with special needs. The study was conducted in several special needs schools in Batam City involving school principals, teachers, administrative staff, parents, and students as research participants. Data were collected through in-depth interviews, observations, and documentation studies, and analyzed using the interactive model of Miles, Huberman, and Saldaña, including data condensation, data display, and conclusion drawing.The findings reveal that educational management strategies significantly contribute to improving student discipline through structured school routines, positive reinforcement, adaptive classroom management, collaborative leadership, and parental involvement. School principals played important roles in coordinating disciplinary programs and creating supportive school cultures, while teachers implemented individualized behavioral approaches adjusted to students’ special needs. The study also found that positive reinforcement and emotional guidance were more effective than punitive approaches in developing discipline among students with disabilities. In addition, supportive learning environments and collaboration between schools and families strengthened students’ behavioral adaptation and compliance with school regulations. However, several challenges were identified, including limited infrastructure, insufficient teacher training, and inconsistent parental involvement. Therefore, strengthening educational management systems, improving teacher competencies, and enhancing collaboration among educational stakeholders are essential for creating sustainable disciplinary cultures in special needs schools.

Mathematical Model Analysis of Disease Spread Using Differential Equations

Christari Lois Palit — 2026-05-19

This study aims to analyze the mathematical model of infectious disease spread using systems of differential equations. Mathematical epidemiology has become an important scientific approach in understanding disease transmission dynamics, predicting epidemic behavior, and evaluating public health intervention strategies. The study employs a mathematical analytical method using the Susceptible–Infected–Recovered (SIR) model to describe interactions among susceptible, infected, and recovered populations over time. The research process includes model formulation, equilibrium point analysis, basic reproduction number analysis, stability analysis, and numerical simulation of disease transmission dynamics. The mathematical model is represented through systems of ordinary differential equations involving transmission and recovery parameters to explain the progression of infectious diseases within a population. The results show that the transmission rate and recovery rate significantly influence epidemic behavior and disease spread intensity. The analysis of the basic reproduction number (R₀)indicates that if R₀>1, the disease spreads rapidly and may lead to an epidemic outbreak, whereas if R₀<1, disease transmission gradually declines and eventually disappears. Stability analysis demonstrates that the disease-free equilibrium is stable when the reproduction number remains below one and unstable when the reproduction number exceeds one. Numerical simulations further illustrate epidemic phases consisting of initial growth, infection peak, and decline phases. The findings confirm that differential equations provide effective mathematical tools for understanding infectious disease dynamics and supporting evidence-based public health decision-making. However, the study also recognizes that simplified epidemiological models possess limitations because real-world disease transmission is influenced by demographic, environmental, behavioral, and social factors. Therefore, further research is recommended to develop more complex and realistic epidemiological models integrating additional variables and computational approaches.