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All Journal Sinergi International Journal of Research and Applied Technology (INJURATECH)
Sari, Annisa Wulan
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Experimental investigation of HHO blending in combustion engine performance Martin, Awaludin; Hidayatullah, Abda; Ginting, Yogie Rinaldy; Sari, Annisa Wulan
SINERGI Vol 29, No 3 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.3.006

Abstract

The transition to renewable energy sources has become increasingly critical due to the adverse effects of greenhouse gas emissions. One alternative to reducing fossil fuel dependence is hydrogen. Hydrogen technology can be integrated into internal combustion engines without major design modifications. This study investigates the effects of HHO gas blending on engine performance under varying brake load conditions. The carburetor was modified to allow HHO gas from electrolysis to enter the combustion chamber. The results indicate that HHO blending led to a 4.9% increase in brake power, a 1.66% improvement in thermal efficiency, and a 3% reduction in brake-specific energy consumption (BSEC). Additionally, among different potassium hydroxide (KOH) concentrations, the 30% wt solution exhibited the lowest power consumption for electrolysis.
The Role of Cloud Computing and Big Data in Enhancing E-Learning Service Quality Sari, Annisa Wulan
International Journal of Research and Applied Technology (INJURATECH) Vol. 5 No. 2 (2025): December 2025
Publisher : Universitas Komputer Indonesia

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Abstract

The transition to digital education has exponentially increased the demand for robust, scalable, and personalized e-learning platforms. Legacy educational systems often struggle with server overloads, limited storage capacity, and the inability to process massive amounts of student data. This study explores the integration of Cloud Computing and Big Data analytics as a strategic solution to enhance e-learning service quality. Through a qualitative approach and thematic analysis of recent literature, this paper identifies that Cloud Computing provides a highly scalable, cost-effective infrastructure that ensures continuous system availability. Concurrently, Big Data empowers educational institutions to analyze student learning behaviors, predict academic outcomes, and deliver personalized learning experiences. The findings suggest that the synergy between these two technologies not only resolves technical bottlenecks but also transforms passive e-learning environments into adaptive, student-centric ecosystems. This study provides a comprehensive framework for higher education institutions aiming to modernize their IT governance and instructional delivery.
Ethics, Trust, and Adoption: A Literature Review on Student Perceptions of Generative AI in Higher Education Sari, Annisa Wulan
International Journal of Research and Applied Technology (INJURATECH) Vol. 5 No. 2 (2025): December 2025
Publisher : Universitas Komputer Indonesia

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The rapid emergence of Generative Artificial Intelligence (GenAI) has sparked a paradigm shift in higher education, placing students at the intersection of technological innovation and ethical ambiguity. This study provides a qualitative systematic review of existing literature to explore the intricate relationship between ethics, trust, and adoption in student perceptions of GenAI. Utilizing a thematic synthesis approach, the research analyzes diverse academic studies to identify recurring patterns in how students navigate these tools. Findings reveal that while GenAI is highly valued for its ability to enhance productivity and personalized learning, adoption is significantly hindered by "ethical anxiety"—concerns regarding academic integrity, data privacy, and the potential loss of critical thinking skills. Trust is identified as a multi-dimensional construct, heavily dependent on institutional transparency and the clarity of AI-usage policies. This review concludes that for GenAI to be successfully integrated, higher education must move beyond functional training toward a framework of ethical literacy. The results offer strategic insights for educators and policymakers to foster a responsible AI-driven academic environment.
Co-Authors Awaludin Martin Ginting, Yogie Rinaldy Hidayatullah, Abda