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All Journal Internet of Things and Artificial Intelligence Journal Jurnal Pengabdian Tri Bhakti
Arrazaq, Fajar
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Social Sciences

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Pengembangan Model Pembelajaran Deep Learning Inovatif Sebagai Pengabdian Masyarakat untuk Meningkatkan Pendidikan Inklusif di Sekolah Menengah Kejuruan Penyelenggara Pendidikan Inklusi Andriana; Zulkarnain; Rahman, Sutisna Abdul; Widjaya, Alfred; Nasrullah, Nanang; Arrazaq, Fajar
Jurnal Pengabdian Tri Bhakti Vol 5 No 2 (2023): Jurnal Pengabdian Tri Bhakti
Publisher : Lembaga Pengabdian kepada Masyarakat Universitas Langlangbuana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36555/jptb.v5i2.2226

Abstract

Inclusive education at Vocational High Schools that offer Inclusive Education (SMK-PPI) aims to provide equal access to learning for students with special needs (SBK). This community service program is designed to develop an innovative Deep Learning-based learning model to enhance inclusivity and the quality of education at SMK-PPI. The program begins with a needs identification phase, where observations and interviews are conducted at schools that accommodate SBK to understand existing challenges and identify gaps in the current teaching methods. Collaboration with the school and community stakeholders is essential to align the program's objectives and tailor the learning plan to meet specific needs. Intensive training for SMK-PPI teachers is the initial step in implementing the program, including the introduction of Deep Learning technology and the development of inclusive teaching strategies. The Deep Learning-based learning model is then implemented in classrooms involving SBK, focusing on personalized learning and using technology to meet individual students' needs. Data is continuously collected through observations, interviews, and surveys to evaluate the program's effectiveness. The evaluation results show that the model successfully increased student engagement, accessibility, and learning outcomes. Reflection and improvement are conducted based on feedback from all involved parties, ensuring that this learning model can be sustainably adopted by other schools. This program is expected to make a significant contribution to strengthening inclusive education at SMK-PPI and helping all students reach their full potential.
NMC Lithium Ion Battery Management with Distributed Monitoring Topology Andriana, Andriana; Rahman, Sutisna Abdul; Arrazaq, Fajar
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 2 (2024): Volume 4 Issue 2, 2024 [May]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i2.739

Abstract

Lithium-ion battery management often called BMS (Battery Management System) is a system that controls all operations between the battery and the required load. The advantages of lithium-ion batteries, such as high energy density and long service life, make them highly desirable. Along with the increase in demand, the use of lithium-ion batteries is also increasingly complex, such as in the use of electric vehicles and smart grids. The battery must have the same voltage as the battery when connected directly. Safety and battery life are at stake if this condition is not met. BMS is a solution to this problem. The purpose of this research is to create a BMS that has three main features: monitoring, balancing, and protection. The Nano Microcontroller can be used to build the BMS. For nickel-based battery types, namely NMC (Nickel Manganese Cobalt) batteries, the design of a battery management system with a distributed monitoring and protection architecture can help battery packs be used for various applications and reduce battery pack production costs.
Co-Authors Alfred Wijaya Andriana Andriana Nasrullah, Nanang Rahman, Sutisna Abdul Zulkarnain Zulkarnain