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All Journal Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika TRANSISTOR Elektro dan Informatika Journal of Electrical Technology UMY JURNAL KAJIAN TEKNIK ELEKTRO JUTEI (Jurnal Terapan Teknologi Informasi) ABDIMAS SILIWANGI GERVASI: Jurnal Pengabdian kepada Masyarakat Jurnal Teknik Elektro dan Komputasi (ELKOM) Journal of Energy and Electrical Engineering (JEEE) E-JOINT (Electronica and Electrical Journal Of Innovation Technology) JITEL (Jurnal Ilmiah Telekomunikasi, Elektronika, dan Listrik Tenaga) EPSILON: Journal of Electrical Engineering and Information Technology International Journal of Advanced Science Computing and Engineering Journal of Computer Engineering, Electronics and Information Technology Gotong Royong Jurnal Pengabdian Siliwangi International Journal of Informatics and Computing Jurnal Teknokes Majalah Ilmiah Teknologi Elektro Jurnal Teknik Elektro
firmansyah maualana sugiartana nursuwars
Jurusan Informatika Universitas Siliwangi Tasikmalaya
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Peningkatan Kualitas Sinyal Photoplethysmography (PPG) melalui Pendekatan Prapemrosesan Multitahap Fitri Handayani; Asep Andang; Firmansyah Maulana Sugiartana Nursuwars
Majalah Ilmiah Teknologi Elektro Vol 24 No 1 (2025): ( Januari - Juni ) Majalah Ilmiah Teknologi Elektro
Publisher : Study Program of Magister Electrical Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MITE.205.v24i01.P06

Abstract

Photoplethysmography (PPG) is a non-invasive technique for measuring various physiological parameters, including blood glucose levels. However, PPG signals are often affected by noise and artefacts that reduce the accuracy of analysis and prediction. Therefore, an effective noise filtering method is needed to make the signal quality and ready for feature extraction for blood glucose estimation. This study offers a solution to the problem of noise in PPG signals through the application of appropriate pre-processing methods. This study aims to select quality PPG signals through three pre-processing methods: detrend, smoothing, and 0.5-5 Hz bandpass filter. The effectiveness of the three methods was evaluated through ADF test to measure the stationarity of the signal, frequency spectrum analysis to observe the distribution of frequency components, and SNR test to assess the signal to noise ratio. Based on the analysis of 67 data samples, the p-value <0.05 was obtained, indicating that the signal has reached a stationary condition. In addition, the average test statistic of men is higher than that of women, indicating that men's signals are more stationary after detrend. Meanwhile, 36 samples (54%) had SNR ≥ 20 dB indicating that more than half of the data were of good enough quality for further analysis. The results show that multi-stage pre-processing improves the quality of PPG signals, validated through quantitative tests of stationarity and SNR values. Thus, the preprocessed and improved quality PPG signals are considered feasible for use in the development of estimation models for various physiological parameters, including blood glucose levels.
Performance Evaluation of a Smart Aeration System for Tilapia Farming Based on IoT and Environmental Sensing Nursuwars, Firmansyah maulana sugiartana; Shofa, Rahmi; hiron, Nurul; Swamardika, Ida Bagus Alit; sambas, aceng
Jurnal Teknokes Vol. 18 No. 4 (2025): Desember
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jteknokes.v18i4.129

Abstract

Fluctuations in dissolved oxygen (DO) levels in high-density biofloc-based tilapia aquaculture pose a critical challenge that directly affects fish growth, survival rate, and feed conversion efficiency. Traditional aeration systems that operate continuously are energy inefficient and unable to adapt dynamically to real-time environmental variations. This study aims to improve DO stability and energy efficiency in biofloc-based tilapia aquaculture through adaptive aeration control. This study designs and evaluates an Internet of Things (IoT)-based smart aeration system that automatically regulates aeration intensity based on real-time DO sensing and threshold-based control logic. The system is built on an ESP32 microcontroller integrated with a digital DO sensor, a water temperature sensor, and relay actuators for blower control, with data transmission via the MQTT protocol and real-time monitoring through a web-based dashboard. Experimental testing was conducted for seven days in a biofloc pond containing 200 tilapia, with a comparative analysis between manual and automated control modes. The results demonstrate that the smart aeration system effectively maintained DO within the optimal range of 5.1–6.8 mg/L while reducing blower energy consumption by 26.7%. Communication reliability was validated with an average transmission delay of 740 ms and a packet loss rate of 1.8%, both of which are acceptable for real-time IoT applications. Data analysis showed consistent improvements in DO stability and energy efficiency throughout the experimental stage. In addition, the system’s modular architecture enables scalability for integration with additional sensors or renewable energy sources, such as solar panels, to support off-grid operations. The findings affirm that the proposed system offers a practical, low-cost, and sustainable solution for data-driven aquaculture management and contribute to the advancement of smart, environmentally responsive aquaculture systems.
Adaptation in IoT-Fog Data Transmission: SLR and Future Perspectives on Dynamic Frequency Control Firmansyah Maulana Sugiartana Nursuwars; Linawati; Nyoman Putra Sastra; Wiharta, Dewa Made; Aceng Sambas
Jurnal Teknik Elektro Vol. 17 No. 1 (2025)
Publisher : LPPM Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jte.v17i1.30564

Abstract

The advancement of Internet of Things (IoT) and fog computing technologies has created significant opportunities for more efficient, faster, and proximity-based data management. However, IoT-Fog systems face considerable challenges related to device heterogeneity, traffic dynamics, and the complexity of network topologies that continuously change. This study conducts a Systematic Literature Review (SLR) of various research works covering dynamic scheduling, routing, context-aware data flow, offloading, and IoT-Fog systems without adaptive mechanisms. The findings indicate that most existing approaches still rely on relatively static topology assumptions, rendering them insufficiently adaptive to real-time changes in network conditions. One area identified as a research gap is dynamic frequency control, an adaptive mechanism capable of dynamically adjusting data transmission intensity based on network conditions. The main conclusion of this study emphasizes the necessity for developing adaptive systems that are topology-agnostic and supported by dynamic frequency control to maintain optimal performance even under significant topology changes. Such systems are anticipated to become a crucial foundation for future IoT-Fog applications, including smart cities, Industry 4.0, and intelligent healthcare services, which demand high reliability and low latency.
Co-Authors Abdul Chobir Aceng Sambas Aceng Sambas, Aceng Ade Sarah Ahmad Hamdan Aji Fauzi Pangestu Alauddin, Rifki Akmal Andhy Romdani, Andhy ANDI NAHRUL HAYAT, MOHAMMAD EXCEL Andri Ulus Rahayu Anshary , Muhammad Adi Khairul Aripin Aripin Aripin Aripin Asep Andang, Asep Dani Gilang Sujana Dewa Made Wiharta Edvin Priatna Enov Tikupasang Fahmi Fathurrohman Fajar Awaludin Fajar Nurohman Faridah, Linda Fitri Handayani Gilang Ramadhani Gunawan, Rohmat Gustaman, Rian Arie Ida Bagus A. Swamardika Ifkar Ushar Imam Taufiqurrahman Imam Taufiqurrahman Jamaluddin Laksana, Angga Linawati Mochammad Fadillah Putra Muhamad Taufik Hidayat Muhammad Arif Ramdani Muhammad Arif Ramdani Muhammad Faiz Dzaki Chanafi Neng Ika Kurniati Nurul Hiron Nurul Hiron, Nurul Nyoman Putra Sastra Permana, Prama Priyatna, Rendi Putri Apriliani Tri Santosa Rendi Priyatna Reza Fragaria Audika Rianto Rianto Risnandar, Muhammad Aris Rohmat Gunawan Shofa, Rahmi Shofa, Rahmi Nur Shopa, Rahmi Nur Silviani, Veni Siti Ratnasari Stheven Erlangga Sanjaya Sulastri, Heni Suryanto, Suyanto Sutisna Sutisna Sutisna Sutisna Sutisna Usrah, Ifkar