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All Journal Kompak : Jurnal Ilmiah Komputerisasi Akuntansi E-Bisnis : Jurnal Ilmiah Ekonomi dan Bisnis Elkom: Jurnal Elektronika dan Komputer CIRCUIT: Jurnal Ilmiah Pendidikan Teknik Elektro IKRA-ITH Informatika : Jurnal Komputer dan Informatika INTECOMS: Journal of Information Technology and Computer Science Budimas : Jurnal Pengabdian Masyarakat Jurnal Teknologi Informasi dan Komunikasi Walisongo Journal of Information Technology Jurnal Informatika Dan Tekonologi Komputer (JITEK) INFORMATIKA Jurnal Universal Technic Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Jurnal Teknik Informatika dan Teknologi Informasi Jurnal Informatika Jurnal Manajemen Informatika & Teknologi JUSIFOR : Jurnal Sistem Informasi dan Informatika Jurnal Ilmiah Teknik Informatika dan Komunikasi Community: Jurnal Pengabdian Pada Masyarakat JURNAL ILMIAH SAINS TEKNOLOGI DAN INFORMASI Jurnal Sistem Informasi Galuh Akuntansi: Jurnal Riset Ilmu Akuntansi Journal of Technology Informatics and Engineering Jurnal Penelitian Teknologi Informasi dan Sains Jurnal Ilmiah Sistem Informasi Jurnal Riset Teknik Komputer Jurnal Padamu Negeri Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Mars: Jurnal Teknik Mesin, Industri, Elektro dan Ilmu Komputer Saturnus: Jurnal Teknologi dan Sistem Informasi International Journal of Economics and Management Research Jurnal Informatika Dan Tekonologi Komputer KREATIF: Jurnal Pengabdian Masyarakat Nusantara Journal of Engineering, Electrical and Informatics Jurnal Teknik Informatika dan Teknologi Informasi Sinov : Media Informasi Penelitian Kabupaten Semarang
Iman Saufik Suasana
Universitas Sains Dan Teknologi Komputer
Religion Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Social Sciences Transportation Other

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Journal : journal of technology informatics and engineering

 1 
APPLICATION OF SOLAR ENERGY TO MEASURE PHOTOVOLTAIC CAPACITY AND BATTERY OPTIMIZATION Unang Achlison; Iman Saufik Suasana; Dendy Kurniawan
Journal of Technology Informatics and Engineering Vol 1 No 1 (2022): April: Journal of Technology Informatics and Engineering
Publisher : Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v1i1.145

Abstract

This study uses the Markov Decision Model (MDP) to implement battery degradation and optimize battery use in Photovoltaic and the battery system model created. The battery optimization scheme for home loads uses the application of solar energy to optimally measure photovoltaic and battery capacity against each other. The different qualities of the standard used in this study are described starting from system characteristics and charge settings to an analysis of MDP and battery degeneration. Various systems undergo a list of analyses to implement awareness reasoning although developing battery volume and photovoltaic for the current system. The parametric span of cosmic and battery central tariff, the tariff of power worn taken away the framework, tariff of battery degeneration, time of year, photovoltaic generator size, battery size, and Health Status (SoH) of batteries were carried out to determine the optimal volume estimate and analyze the trade-offs essential in a mix scheme. This is then used to treasure trove the minimum amount of fee of the scheme with photovoltaic and battery application. This study support decision of the essential sizing deliberation for photovoltaic and battery-managed home loads linked to the services grid. Insightful that the battery can be used more destructively, also it can be formed lower and run at a greater C speed. This study analyzes actual fog computing research tools and storage composition algorithms for fog computing and develops a fog computing monitoring framework to provide data for fog computing storage composition algorithms. The framework proposed in this study provides granular container virtual hardware resource information and black box monitoring of service layer information associated with microservices. Framework usefulness on Raspberry Pis and CPU overhead of framework tested. The results of this study present the framework proposed could be used on single-chip microcomputers with relatively inadequate computational performance. In addition, a minimal effect on the battery degeneration system on the MDP decision due to the low system C-rate limit for the battery and interesting behavior of total fee and demand is also found. For future research, testing different maximum C levels should be considered to determine the photovoltaic size and battery system affected. Various battery optimization systems can be proved to check the benefit and disbenefits in the microgrid system case study. Lastly, collecting a scheme for actual-time reproduction to know how nice the operation is performing is the next stage of implementing MDP for battery management and system development.
APPLICATION OF SOLAR ENERGY TO MEASURE PHOTOVOLTAIC CAPACITY AND BATTERY OPTIMIZATION Unang Achlison; Iman Saufik Suasana; Dendy Kurniawan
Journal of Technology Informatics and Engineering Vol 1 No 1 (2022): April: Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v1i1.145

Abstract

This study uses the Markov Decision Model (MDP) to implement battery degradation and optimize battery use in Photovoltaic and the battery system model created. The battery optimization scheme for home loads uses the application of solar energy to optimally measure photovoltaic and battery capacity against each other. The different qualities of the standard used in this study are described starting from system characteristics and charge settings to an analysis of MDP and battery degeneration. Various systems undergo a list of analyses to implement awareness reasoning although developing battery volume and photovoltaic for the current system. The parametric span of cosmic and battery central tariff, the tariff of power worn taken away the framework, tariff of battery degeneration, time of year, photovoltaic generator size, battery size, and Health Status (SoH) of batteries were carried out to determine the optimal volume estimate and analyze the trade-offs essential in a mix scheme. This is then used to treasure trove the minimum amount of fee of the scheme with photovoltaic and battery application. This study support decision of the essential sizing deliberation for photovoltaic and battery-managed home loads linked to the services grid. Insightful that the battery can be used more destructively, also it can be formed lower and run at a greater C speed. This study analyzes actual fog computing research tools and storage composition algorithms for fog computing and develops a fog computing monitoring framework to provide data for fog computing storage composition algorithms. The framework proposed in this study provides granular container virtual hardware resource information and black box monitoring of service layer information associated with microservices. Framework usefulness on Raspberry Pis and CPU overhead of framework tested. The results of this study present the framework proposed could be used on single-chip microcomputers with relatively inadequate computational performance. In addition, a minimal effect on the battery degeneration system on the MDP decision due to the low system C-rate limit for the battery and interesting behavior of total fee and demand is also found. For future research, testing different maximum C levels should be considered to determine the photovoltaic size and battery system affected. Various battery optimization systems can be proved to check the benefit and disbenefits in the microgrid system case study. Lastly, collecting a scheme for actual-time reproduction to know how nice the operation is performing is the next stage of implementing MDP for battery management and system development.
APPLICATION OF SOLAR ENERGY TO MEASURE PHOTOVOLTAIC CAPACITY AND BATTERY OPTIMIZATION Unang Achlison; Iman Saufik Suasana; Dendy Kurniawan
Journal of Technology Informatics and Engineering Vol. 1 No. 1 (2022): April: Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v1i1.145

Abstract

This study uses the Markov Decision Model (MDP) to implement battery degradation and optimize battery use in Photovoltaic and the battery system model created. The battery optimization scheme for home loads uses the application of solar energy to optimally measure photovoltaic and battery capacity against each other. The different qualities of the standard used in this study are described starting from system characteristics and charge settings to an analysis of MDP and battery degeneration. Various systems undergo a list of analyses to implement awareness reasoning although developing battery volume and photovoltaic for the current system. The parametric span of cosmic and battery central tariff, the tariff of power worn taken away the framework, tariff of battery degeneration, time of year, photovoltaic generator size, battery size, and Health Status (SoH) of batteries were carried out to determine the optimal volume estimate and analyze the trade-offs essential in a mix scheme. This is then used to treasure trove the minimum amount of fee of the scheme with photovoltaic and battery application. This study support decision of the essential sizing deliberation for photovoltaic and battery-managed home loads linked to the services grid. Insightful that the battery can be used more destructively, also it can be formed lower and run at a greater C speed. This study analyzes actual fog computing research tools and storage composition algorithms for fog computing and develops a fog computing monitoring framework to provide data for fog computing storage composition algorithms. The framework proposed in this study provides granular container virtual hardware resource information and black box monitoring of service layer information associated with microservices. Framework usefulness on Raspberry Pis and CPU overhead of framework tested. The results of this study present the framework proposed could be used on single-chip microcomputers with relatively inadequate computational performance. In addition, a minimal effect on the battery degeneration system on the MDP decision due to the low system C-rate limit for the battery and interesting behavior of total fee and demand is also found. For future research, testing different maximum C levels should be considered to determine the photovoltaic size and battery system affected. Various battery optimization systems can be proved to check the benefit and disbenefits in the microgrid system case study. Lastly, collecting a scheme for actual-time reproduction to know how nice the operation is performing is the next stage of implementing MDP for battery management and system development.
Integrating Big Data and Edge Computing for Enhancing AI Efficiency in Real-Time Applications Susatyono, Jarot Dian; Suasana, Iman Saufik; Rozikin, Khoirur
Journal of Technology Informatics and Engineering Vol. 3 No. 3 (2024): December (Special Issue: Big Data Analytics) | JTIE: Journal of Technology Info
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i3.204

Abstract

Integrating Big Data and Edge Computing is revolutionizing the efficiency of artificial intelligence (AI) systems, particularly in applications requiring real-time responses. This study explores the synergistic role of these technologies in two critical sectors: autonomous vehicles and healthcare. Using a case study approach, real-world datasets and simulation platforms were employed to evaluate improvements in latency, prediction accuracy, and system efficiency. Key findings reveal that Edge Computing reduces latency by 30%, with response times dropping from 150 ms to 105 ms in autonomous vehicles and from 200 ms to 140 ms in healthcare applications. Additionally, leveraging Big Data for AI training enhanced prediction accuracy by 15% for traffic pattern recognition and 12% for patient condition monitoring. Despite these advancements, challenges such as scalability, data security, and interoperability persist, necessitating robust infrastructure and end-to-end encryption solutions. This research highlights the transformative potential of combining Big Data and Edge Computing to optimize AI systems for real-time applications, offering insights into improving operational efficiency and predictive accuracy. The findings are expected to guide future developments in AI technologies, particularly in the context of expanding 5G networks and growing demand for real-time data processing.  
Co-Authors Abdul Jamil Adi Suryo Ramadhan Agus Windarto Ahmad Ashifuddin Aqham Al Fatkurrozak Al Fatkurrozak Aldo Raditya Pangestu Andre maulana Andre maulana Anthony Hermansya Putra Arreli Gavin Dewangga Laksana Arsito Ari Kuncoro Ayyub Hamdanu Budi Nurmana Beltsazaran Beltsazaran budi hartono Budi Hartono Catur Wahyu Aji Siswoyo Danang Danang Danang, Danang Dani Sasmoko Dani sasmoko Dendy Kurniawan Dendy Kurniawan Dendy Kurniawan Edy Siswanto Eka Bagus Ekky Fredyan Eryan Ahmad Firdaus Farhan Afif Ilmi Febrian Wahyu Christanto Febryantahanuji Febryantahanuji Firdaus Febriansyah Haqqi Surya Wicaksono Hondor Saragih Hudha Pratna Safiyan Ilham Febrianto Irdha Yunianto Jarot Dian Susatyono Julitta Dewayani Kasih Purwantini Katon Abdul Fatah Katon Abdul Fatah Khoirur Rozikin Khoirur Rozikin Khoirur Rozikin Khoirur Rozikin Lutfi, Maula Raditya Lutmawati Lutmawati Lutmawati Lutmawati M. Andi Prio Santoso Migunani Migunani Mochamad Januaridwan Mohamad Balya Muhammad Ainun Najib Muhammad Miftahhudin Muhammad Ryza Awwali , Sulartopo, Muhammad Ryza Awwali , Muhammad, Rasul Louise Naufal Rizki, Muhammad Nesa Adinda Nur Afifah Nur Cahyo Hendro Wibowo Nur Hidayatus Shofyan Nuris Dwi Setiawan Nuris Dwi Setiawan Nurjanah, Putri Rafael Ardian Fahrezi Ridho Haqqi Santoso Ririn Ratna Cahyanti Risky Hardiwiranto Rizky Aji Prasetyo Rizky Aji Prasetyo Rosalina Wahyuningsih Rusito Ryan Michael Wijoyo Sandi Yoni Saputra Santi Widiastuti Santoso, Agustinus Budi Santoso Setyo Aji Pamungkas Shanti Maulani Siswanto Siswanto Siswanto, Edy Sulartopo Sulartopo Sulartopo Sulartopo Sumaryanto Susatyono, Jarot Dian Teguh Setiadi Toni Wijanarko Adi Putra Tony Winjanarko Adi Putra Ummi Hanik Unang Achlison Wicaksono, Yusril Ahda Widya Ariyani Widya Ariyani Zaenal Mustofa Zahra Dinul Haq Zahra Dinul Haq Zumroasih Zumroasih