Scientechno: Journal of Science and Technology

Strategies for Improving Literacy and Numeracy in Computer-Based National Assessment at Madrasah Ibtidaiyah

Tri Asihati Ratna Hapsari, Dede Rosyada, N. Oneng Nurul Bariyah — Wed, 12 Mar 2025 00:00:00 +0700

This study aims to identify and analyze strategies for improving literacy and numeracy in response to the Computer-Based National Assessment (ANBK) at Madrasah Ibtidaiyah Pembangunan Universitas Indonesia, Jakarta. National assessment results show that students’ literacy and numeracy skills still require improvement to meet established standards. The research investigates strategies employed by madrasahs through intracurricular and extracurricular activities, along with the use of technological infrastructure to enhance students’ literacy and numeracy outcomes. A descriptive approach with qualitative data analysis was used, involving observation, interviews, and documentation. Findings reveal strategies such as integrating literacy into learning, applying problem-based learning, and utilizing technology in assessments. Extracurricular activities like school literacy movements and technology-based numeracy training also contribute to better performance in the Computer-Based National Assessment. The study concludes that strengthening literacy and numeracy-focused learning strategies can boost students’ competencies in understanding and applying academic concepts. Effective collaboration among teachers, students, and policymakers is crucial for optimizing literacy and numeracy improvement strategies, creating a Smart Madrasah with Smart Learning & Assessment and a Digital Ecosystem that fosters innovative, inclusive educational environments.

The Importance of Personnel Planning and Infrastructure in Supporting Work Effectiveness at Ar-Rahman IT SMP Lareh Sago Halaban

Nova Nova, Januar Januar, Ulva Rahmi, Yusrawati Yusrawati — Fri, 21 Mar 2025 00:00:00 +0700

This study aims to emphasize the importance of staffing planning and facilities in improving work effectiveness at SMP IT Ar-Rahman Lareh Sago Halaban, in the field of education, work effectiveness is highly dependent on the availability of a competent workforce and adequate facilities. This research uses a qualitative approach with a case study method at SMP IT Ar-Rahman Lareh Sago Halaban. Data were obtained through interviews, observation, and document analysis. The results showed that good staffing planning, including recruitment, training and staff development, plays a significant role in improving the performance of teachers and school staff. In addition, adequate facilities, such as comfortable classrooms, well-equipped laboratories and other supporting facilities, are also very important for creating a conducive learning environment. The findings emphasize that integrated and sustainable planning in terms of staffing and facilities is key to improving work effectiveness at SMP IT Ar-Rahman Lareh Sago Halaban. Therefore, schools need to continuously improve efforts in planning and managing human resources and educational facilities to achieve optimal educational goals.

Utilization and Evaluation of Virtual Reality and Simulations in Teaching-Learning Direct Current Circuits

Tue, 08 Apr 2025 00:00:00 +0700

This study evaluates the effectiveness of integrating Virtual Reality (VR) and simulation in teaching direct current (DC) circuits. VR and simulation provide interactive spaces for students to learn, manipulate components, and conduct experiments, thereby enhancing motivation and engagement. The study employs a quasi-experimental design with control and experimental groups. The participants were assessed through pretests and posttests. Pretest results of both groups reveals no significant difference which suggests similar baseline abilities and level of knowledge in relation to DC circuits. The pretest and posttest results showed a significant difference which suggest that after the intervention, both groups showed a significant improvement in their knowledge of Direct Current Circuits. However, posttest results also showed a marked improvement of the experimental group using VR and simulation compared to the control group, supporting the effectiveness of integrating VR and simulation in teaching DC circuits. This suggests that VR and simulation can be valuable resources in instructional delivery, facilitating a deeper understanding and mastery of electrical concepts.

Utilization of the Microbiome to Increase Food Security Throught Sustainable Biotechnology

Muhammad Hazmi, Seo Jiwon, Ruby Kingh — Sat, 12 Apr 2025 00:00:00 +0700

Food security remains a critical global challenge, requiring innovative and sustainable solutions to meet the growing demand for nutritious food. One promising approach is the utilization of microbiomes in sustainable biotechnology to enhance agricultural productivity, improve soil health, and increase food production efficiency. This study aims to explore the potential of microbiome-based biotechnological applications in strengthening food security through sustainable agricultural practices. A qualitative research methodology was employed, involving an extensive literature review and analysis of case studies related to microbiome utilization in agriculture. The findings indicate that microbiomes play a significant role in improving crop resilience, enhancing nutrient absorption, and reducing the need for chemical fertilizers and pesticides. Furthermore, microbiome-based biotechnology contributes to environmental sustainability by promoting soil biodiversity and reducing greenhouse gas emissions. The study concludes that integrating microbiome technology into agricultural systems can significantly enhance food security while ensuring ecological balance. Future research should focus on optimizing microbiome applications and developing scalable implementation strategies for various agricultural settings.

Pattern Recognition System for Automating Medical Diagnosis Based on Image Data

Evi Irianti, Nina Anis, Saifiullah Aziz — Sat, 12 Apr 2025 00:00:00 +0700

The increasing volume and complexity of medical image data have presented significant challenges for healthcare professionals in delivering timely and accurate diagnoses. Traditional diagnostic processes are often time-consuming and prone to human error, underscoring the need for automated solutions. This study aims to develop a pattern recognition system to automate medical diagnosis using image data, thereby improving diagnostic accuracy and efficiency. A hybrid methodology was employed, combining image preprocessing, feature extraction using convolutional neural networks (CNNs), and classification through deep learning algorithms. The system was trained and validated using publicly available medical image datasets across various disease types. The results demonstrate high diagnostic accuracy, with the system achieving over 92% precision in identifying disease patterns from image inputs. Furthermore, the model exhibited robustness across different imaging modalities, such as X-rays, MRIs, and CT scans. These findings suggest that the proposed pattern recognition system can serve as a reliable support tool for medical practitioners. In conclusion, the integration of image-based pattern recognition in medical diagnostics holds significant promise in enhancing clinical decision-making processes and reducing diagnostic errors.