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All Journal Jurnal Teknik Elektro CESS (Journal of Computer Engineering, System and Science) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Techne : Jurnal Ilmiah Elektroteknika Cyber Security dan Forensik Digital (CSFD) Jurnal Teknik Informatika (JUTIF) Jurnal Energi Baru dan Terbarukan Electron: Jurnal Ilmiah Teknik Elektro Sainteknol : Jurnal Sains dan Teknologi Edu Elektrika Journal Journal of Soft Computing Exploration
Aprilianto, Rizky Ajie
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Environmental Science Other

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Integrasi Cron Job untuk Otomatisasi Pengolahan dan Transfer Data pada Sistem Cloud-Fog Wibowo, Apriansyah; Fathimah, Aisya; Aprilianto, Rizky Ajie; Waskito, Deswal
Edu Elektrika Journal Vol. 12 No. 2 (2024)
Publisher : LPPM Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/2k6j4w06

Abstract

Perkembangan pesat perangkat Internet of Things (IoT) telah menghasilkan peningkatan signifikan dalam volume data, yang menciptakan tantangan dalam pemrosesan data secara real-time.  Meskipun sistem cloud-fog dapat mengurangi latensi dengan memproses data lebih dekat ke sumbernya, pengelolaan dan transfer data tetap bergantung pada tugas terjadwal yang efisien. Penelitian ini bertujuan untuk mengurangi intervensi manual dan meningkatkan efisiensi sistem melalui penggunaan cron job yang dikonfigurasi dengan logika skrip PHP dan diimplementasikan di Cloud Panel. Sistem ini dirancang untuk menjadwalkan transfer data secara otomatis dengan interval yang disesuaikan dan memastikan pembaruan data yang tepat waktu dalam lingkungan cloud-fog. Hasil penelitian menunjukkan bahwa penerapan otomatisasi transfer data berhasil mengurangi kesalahan, meningkatkan efisiensi, dan memastikan pembaruan data yang lebih tepat waktu dalam sistem cloud-fog
Design of ACS712-based Current Sensing Monitoring Evaluation for PWM Solar Charge Controller Wibowo, Apriansyah; Jayendra, I Gede Bagus; Utari, Dhea Yunita; Rasyiid, Muhammad; Aprilianto, Rizky Ajie
Sainteknol : Jurnal Sains dan Teknologi Vol. 22 No. 2 (2024): December 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sainteknol.v22i2.20604

Abstract

The rise of renewable energy has led to growing interest among researchers in optimizing renewable energy systems to harvest the highest possible energy output, especially in photovoltaic (PV) systems. Photovoltaic systems generate energy from sunlight, but the intermittent nature of sunlight poses a challenge for providing constant power. Another problem is that the most affordable conventional Pulse-Width Modulation (PWM) controllers on the market are unable to provide a current monitoring system. This issue is critical when users require detailed data to perform diagnostics on their PV systems. In this study, a monitoring system using microcontrollers and the ACS712 current sensor was developed and implemented to observe the behavior and performance of a photovoltaic (PV) charging system based on the current output from a PWM controller. The primary objective of this system is to develop a solution that can identify PV modules operating under suboptimal conditions, which can be caused by various factors such as increased solar cell temperature, cloud cover effects, PV module degradation, and the performance of the Pulse-Width Modulation (PWM) solar charge controller (SCC). This is crucial because PV modules can be susceptible to various environmental and technical factors that may impact their efficiency and power output. By closely monitoring the performance of each PV module using the ACS712-based current sensing system, the researchers aim to promptly detect and address any issues that may arise, ensuring the overall optimal operation of the PV system.
Pengembangan Intelligent Electrocardiograph Portable untuk Pemantauan Detak Jantung: Systematic Literature Review Hardi, Septian Akbar Noor Wahyu; Aviando, Rizqi; Pribadi, Feddy Setio; Aprilianto, Rizky Ajie
CESS (Journal of Computer Engineering, System and Science) Vol. 9 No. 2 (2024): July 2024
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v9i2.59003

Abstract

Kesehatan jantung menjadi faktor penting yang harus diperhatikan, terutama pada orang yang melakukan aktivitas fisik tinggi, seperti atlet. Untuk meningkatkan identifikasi dini penyakit jantung dan mengurangi bahaya kematian mendadak, perangkat elektrokardiogram (EKG) cerdas portabel telah banyak diusulkan untuk mendeteksi aktivitas jantung secara real-time. Penelitian ini bertujuan untuk memberikan informasi tentang klasifikasi sinyal jantung dengan memanfaatkan Filter Infinite Impulse Response (IIR) untuk menghilangkan noise sinyal dan Random Forest yang berguna untuk mengkategorikan masalah jantung secara cepat dan akurat. Referensi yang dirujuk, dipetakan berdasarkan sistematic literature review menggunakan metode preferred reporting items for systematic reviews and meta-analyses (PRISMA). Berdasarkan hasil ulasan yang telah dilakukan, terbukti EKG portable dengan filter IIR terbukti mampu membersihkan sinyal yang didukung dengan algoritma Random Forest untuk klasifikasi sehingga menghasilkan tingkat akurasi yang baik.
Bio-inspired metaheuristic MPPT algorithms for PV battery systems: a comparative performance study Faqih, Faiq Mananul; Aprilianto, Rizky Ajie
Journal of Soft Computing Exploration Vol. 7 No. 1 (2026): March 2026
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v7i1.13

Abstract

Maximum Power Point Tracking (MPPT) has been proven to improve power extraction in photovoltaic (PV) systems. However, conventional MPPT methods such as Perturb and Observe (P&O) and Incremental Conductance (InC) have limitations, such as oscillations in steady state conditions, slow response, and a tendency to get stuck at local maxima when irradiation changes. This study aims to evaluate biology-inspired metaheuristic algorithms to improve tracking accuracy, convergence speed, and MPPT stability in PV systems. These algorithms include Grey Wolf Optimization (GWO), Sand Cat Swarm Optimization (SCSO), Horse Herd Optimization (HHO), Chameleon Swarm Algorithm (CSA), and Flying Squirrel Search Optimization (FSSO). The algorithms were tested using the same general parameters to ensure a fair comparison. Testing was conducted on PV models, DC boost converters with resistive loads and batteries under static and dynamic irradiation conditions using MATLAB/Simulink. The results show that HHO provides the best performance with an efficiency of 99.96% at 1000 W/m² and 98.03% at 800 W/m², a tracking time of <0.05 seconds, and power fluctuations of <0.3% in resistive load testing. In battery testing, CSA and FSSO showed the best performance with voltage stability, high charging current, and lower ripple. Overall, the results of this study indicate that the proposed metaheuristic-based MPPT algorithm can improve the accuracy of maximum power point tracking, accelerate convergence time, and minimize power oscillations in PV systems.
Co-Authors Adiastoro, Mahendra Al Kindi, Bilal Alkindi, Muhammad Faizal Ananda, Briska Putra Anita, Nur Ariefianto, Rizki Mendung Arundaya, Adil Ati Zuhrotal Afifah, Ning Imas Aviando, Rizqi DZAKWAN, MUHAMAD AKMAL Fahreza, Rizqy Achmad Faqih, Faiq Mananul Fathimah, Aisya Feddy Setio Pribadi Hardi, Septian Akbar Noor Wahyu Heri Suryoatmojo Jayendra, I Gede Bagus Mario Norman Syah, Mario Norman Nurul'aini, Arvina Rizqi Pongoh, Arthur Gregorius Rasyiid, Muhammad Suwito Suwito Syarifah, Dian Farah Utari, Dhea Yunita Waskito, Deswal Wibowo, Apriansyah