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Simulation Of Electrical Load With An Over Load System Shedding Winardi, Bambang; Sinuraya, Enda Wista; Karnoto, Karnoto; ZM, Ajub Ajulian
Engineering and Technology International Journal Vol 6 No 01 (2024): Engineering and Technology International Journal (EATIJ)
Publisher : YCMM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55642/eatij.v6i01.654

Abstract

A break in one of the circuits in a double circuit transmission network system can cause the system to overload. Where excess load on the transmission network system can cause quite dangerous impacts. The Over Load Shedding system is a protection system for the electric power transmission network which aims to prevent widespread blackouts by removing certain predetermined loads. By using the Arduino Mega 2560 as a control center, security against load abnormalities can be carried out and can be monitored automatically using Scada, apart from that, PMT taping for load balancing can also be done using Scada. The Arduino Mega 2560 will read the current on each phase wire using the ACS712 current sensor to detect the load of one of the circuits to be aware of whether it is overloaded or not. This simulator tool has carried out several measurements and tested how to operate it. This tool has a fairly high level of work accuracy, reaching 85% success in operation. So it is hoped that this tool can provide knowledge to the wider community about over load shedding systems in maintaining the electric power transmission system properly and easily to understand.
The Effect of AI Technology, Innovation Readiness, and Digital Entrepreneurship on Competitive Advantage in Start Up in Jakarta Bakri, Bakri; ZM, Ajub Ajulian; Defitri, Siska Yulia; Mu'min, Halek
West Science Interdisciplinary Studies Vol. 2 No. 04 (2024): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v2i04.807

Abstract

This study investigates the impact of AI technology adoption, innovation readiness, and digital entrepreneurship on competitive advantage in startup enterprises within Jakarta's entrepreneurial ecosystem. A quantitative approach employing Structural Equation Modeling (SEM) with Partial Least Squares (PLS) analysis was utilized to analyze data collected from 229 startup founders and executives. The findings reveal significant positive relationships between AI technology adoption, innovation readiness, digital entrepreneurship, and competitive advantage. Specifically, startups that strategically embrace AI technologies, foster innovation readiness, and leverage digital entrepreneurship practices demonstrate higher levels of competitive advantage. The study contributes to theoretical understanding by extending literature on technology-driven entrepreneurship and provides practical insights for startup stakeholders and policymakers aiming to enhance the competitiveness of Jakarta's startup ecosystem.
The Role of Wind Power Plant in Energy Transition towards Net Zero Emission Judijanto, Loso; ZM, Ajub Ajulian; Winardi, Bambang; Joni, Joni
West Science Information System and Technology Vol. 3 No. 01 (2025): West Science Information System and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsist.v3i01.1847

Abstract

This literature review explores the role of wind power plants in the global transition towards zero emissions, synthesizing insights from 20 Scopus-indexed articles. The review highlights technological advancements in turbine design, offshore wind power, and energy storage solutions, which enhance wind power efficiency and reliability. It also examines the critical role of supportive policies, such as feed-in tariffs and power purchase agreements, in fostering wind energy growth. Environmental impacts, particularly regarding wildlife and ecosystem disruptions, are considered, alongside strategies to mitigate these effects. Furthermore, the economic viability of wind power is assessed, with a focus on cost reduction, job creation, and local economic development. Finally, the integration of wind power into existing energy grids is discussed, emphasizing the need for grid modernization and storage solutions. The review concludes that wind power is a central component of a zero-emissions energy system, though challenges remain in its widespread adoption and integration.
The Effect of Temperature and Weather Conditions on the Performance of Photovoltaic Modules in Tropical Indonesia ZM, Ajub Ajulian; Sinuraya, Enda Wista; Winardi, Bambang
West Science Information System and Technology Vol. 3 No. 01 (2025): West Science Information System and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsist.v3i01.1870

Abstract

This study explores the effect of temperature and weather conditions on the performance of photovoltaic (PV) modules in tropical Indonesia, utilizing a qualitative approach with interviews from five solar energy professionals. The research identifies key environmental factors such as high temperatures, humidity, and rainfall as significant influences on PV module efficiency. Participants noted that elevated temperatures reduce energy output by causing thermal losses, while high humidity and rainfall lead to dust accumulation and reduced sunlight exposure, further affecting efficiency. Additionally, challenges related to corrosion and dust accumulation were highlighted, particularly in coastal and inland regions. The study also suggests various strategies, including the use of anti-reflective coatings, cooling systems, and optimal panel placement, to mitigate these effects. Regional variations in climate necessitate site-specific maintenance and design strategies. This research provides important insights into optimizing PV system performance in tropical climates and emphasizes the need for tailored approaches in PV design and maintenance.
The Role of Federated Learning in Enhancing Data Privacy in Distributed Environments in Indonesia ZM, Ajub Ajulian; Sinuraya, Enda Wista; Winardi, Bambang
The Eastasouth Journal of Information System and Computer Science Vol. 3 No. 01 (2025): The Eastasouth Journal of Information System and Computer Science (ESISCS)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/esiscs.v3i01.720

Abstract

This study investigates the role of federated learning (FL) in enhancing data privacy within distributed environments in Indonesia. With the increasing reliance on digital technologies, data privacy has become a critical concern, particularly in decentralized systems. A quantitative research approach was employed, involving 130 respondents from various professional backgrounds engaged with distributed data systems. Data were collected using a structured questionnaire with a five-point Likert scale (1–5) and analyzed using SPSS version 25. Descriptive, correlation, and regression analyses revealed that federated learning significantly contributes to improving confidentiality, trust, and compliance in distributed environments. The results indicate that FL not only safeguards sensitive data but also enhances stakeholder confidence and supports adherence to regulatory standards, such as Indonesia’s UU PDP. The study provides empirical evidence supporting the adoption of federated learning as a privacy-preserving technology and offers practical insights for organizations and policymakers seeking secure and compliant digital ecosystems.
Analysis of the Trends in AI-as-a-Service (AIaaS) Implementation in Technology Companies in Indonesia Sinuraya, Enda Wista; ZM, Ajub Ajulian; Winardi, Bambang
The Eastasouth Journal of Information System and Computer Science Vol. 3 No. 01 (2025): The Eastasouth Journal of Information System and Computer Science (ESISCS)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/esiscs.v3i01.721

Abstract

This study examines the impact of adoption drivers, perceived benefits, and implementation challenges of Artificial Intelligence-as-a-Service (AIaaS) on the organizational performance of technology companies in Indonesia. Using a quantitative approach, data were collected from 200 respondents through structured questionnaires and analyzed with multiple regression techniques. The results reveal that adoption drivers and perceived benefits have a significant positive influence on organizational performance, while implementation challenges exert a negative impact. These findings suggest that while AIaaS offers considerable potential for efficiency, innovation, and competitive advantage, unresolved barriers such as data security, system integration, and limited human resources hinder its effectiveness. This study contributes to the growing body of literature on AI adoption in emerging economies by highlighting the dual role of enablers and inhibitors in shaping AIaaS outcomes. Practical implications include the need for organizations to invest in digital skills development and risk management, and for policymakers to establish clear regulatory frameworks to accelerate responsible AIaaS adoption in Indonesia.