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Scientechno: Journal of Science and Technology
Published by Yayasan Adra Karima Hubbi
ISSN : 29864887     EISSN : 29637481     DOI : 10.70177/Scientechno
Core Subject :
The journal provides a platform for the publication of original qualitative and quantitative research on education and instruction, compilations based on critical evaluation of current literature, and meta-analysis studies. The Scientechno: Journal of Science and Technology also aims to provide a platform where multiple educational disciplines can contribute and share educational insights, innovative approaches and practices. In this respect, Scientechno: Journal of Science and Technology publishes research in an attempt to present a reliable and respectable information source for the researchers.
Arjuna Subject : -
Articles 4 Documents
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Search results for , issue "vol. 5 no. 1 (2026)" : 4 Documents clear
AN AI-BASED ADAPTIVE LEARNING PLATFORM FOR PERSONALIZED STEM EDUCATION IN INDONESIAN HIGH SCHOOLS Nong Chai; Shahinur Rahman; Tasnia Islam; Ruhul Amin
Scientechno: Journal of Science and Technology Vol. 5 No. 1 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientechno.v5i1.2639

Abstract

In recent years, the demand for personalized education has increased, particularly in Science, Technology, Engineering, and Mathematics (STEM) fields, where students’ learning needs vary significantly. In Indonesia, traditional classroom-based teaching methods struggle to accommodate the diverse learning styles and paces of students. With the rise of Artificial Intelligence (AI), there is a growing opportunity to design adaptive learning platforms that provide personalized learning experiences. However, such platforms are still underutilized in Indonesian high schools, especially in STEM education. This study aims to develop and evaluate an AI-based adaptive learning platform tailored to personalized STEM education for high school students in Indonesia. The platform’s primary goal is to enhance student engagement and academic performance by adapting learning materials and strategies based on individual student progress and preferences. The research utilized a design-based methodology, developing the platform using AI algorithms to monitor and adjust content delivery according to the student’s learning pace, strengths, and weaknesses. A quasi-experimental design was employed, with pre- and post-assessments conducted to evaluate the effectiveness of the platform in a sample of 200 high school students across four Indonesian schools. The platform significantly improved student engagement, with a 15% increase in STEM learning outcomes. Students demonstrated higher retention rates and improved problem-solving abilities, especially in mathematics and science. The AI-based adaptive learning platform proves to be a promising tool for personalized STEM education, enhancing both student learning experiences and academic performance in Indonesian high schools.
USING MACHINE LEARNING TO PREDICT DENGUE FEVER OUTBREAKS IN INDONESIAN URBAN CENTERS BASED ON CLIMATE AND MOBILITY DATA Som Chai; Shahram Rahimov; Dilshod Tursunuv; Gulbahor Alimova
Scientechno: Journal of Science and Technology Vol. 5 No. 1 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientechno.v5i1.2641

Abstract

Dengue fever remains a critical public-health threat in Indonesia’s densely populated urban centers, where climatic fluctuations and human mobility accelerate transmission dynamics. This study aims to develop a predictive model for dengue outbreaks using machine-learning techniques that integrate multi-source climate indicators (temperature, rainfall, humidity) and population-mobility data. A quantitative research design employing supervised learning algorithms including Random Forest, Gradient Boosting, and Long Short-Term Memory (LSTM) networks—was applied to historical datasets from 2015–2023 across six major Indonesian cities. Model performance was evaluated using accuracy, precision, recall, and AUC metrics. Results indicate that the LSTM model achieved the highest predictive accuracy (92.3%) and superior temporal sensitivity to climatic shifts and mobility surges compared with traditional regression models. These findings demonstrate that machine-learning-based early-warning systems can identify outbreak hotspots up to four weeks in advance, providing actionable insights for urban health authorities. The study concludes that integrating climate and mobility analytics enhances the effectiveness of public-health surveillance and supports proactive dengue-control interventions in rapidly urbanizing environments.
CULTIVATING RESILIENCE: A MULTI-LEVEL ANALYSIS OF ORGANIZATIONAL CULTURE AND BUREAUCRATIC AGILITY IN THE FACE OF SYSTEMIC CRISES Mulyaningsih Mulyaningsih
Scientechno: Journal of Science and Technology Vol. 5 No. 1 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientechno.v5i1.3806

Abstract

Organizational resilience has become an essential factor for navigating systemic crises, yet the interplay between organizational culture and bureaucratic agility remains underexplored. This study investigates how these two elements collectively contribute to an organization’s ability to respond to and recover from crises. The main objective of the research is to examine the relationship between organizational culture, bureaucratic agility, and resilience, particularly during systemic crises. A multi-level analysis is conducted through a comparative study across public, private, and non-profit sectors, utilizing both qualitative (interviews and focus groups) and quantitative (surveys) methods. The results show that organizations with a strong, adaptable culture and flexible bureaucratic systems exhibit higher levels of resilience, enabling quicker adaptation and more effective crisis management. The private sector, with its emphasis on innovation and agility, demonstrated superior resilience compared to the more rigid structures found in the public and non-profit sectors. This study concludes that both organizational culture and bureaucratic agility are crucial in cultivating resilience, with their combined influence offering a more effective approach to crisis preparedness and response. The findings underscore the need for organizations to integrate cultural and structural flexibility to enhance resilience in the face of uncertainty.
DIGITAL TRANSFORMATION OF ACCOUNTING THROUGH ARTIFICIAL INTELLIGENCE TECHNOLOGY Rohaeni Marliana; Audy Dea Maharani; Rina Destiana
Scientechno: Journal of Science and Technology Vol. 5 No. 1 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientechno.v5i1.2283

Abstract

Artificial intelligence (AI) has played a crucial role in improving the efficiency and accuracy of financial data management in the accounting field through process automation, big data analysis, and faster and more precise decision-making. This research aims to analyze the perception of accounting students in Indonesia towards the application of artificial intelligence (AI) in the digital transformation of accounting. Using a descriptive quantitative method with a survey of 163 respondents, the results showed that the majority of students understood that AI has been applied in companies and got information from the internet and social media. They agree that AI can automate routine tasks, increase efficiency, and minimize errors in the accounting process. However, the study also revealed concerns regarding potential workforce reductions, over-reliance on technology, and data security risks and skills gaps that could exacerbate social inequality. These findings highlight the importance of improving student competencies and attention to social, ethical, and security aspects in the application of AI so that its benefits can be utilized optimally and responsibly in the digital era.

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