Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal Unes Law Review INFOKUM
Beni Satria
Universitas Pembangunan Panca Budi Medan, North Sumatera, Indonesia
Computer Science & IT Education Law, Crime, Criminology & Criminal Justice Physics Public Health Social Sciences

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Legal Analysis of Legal Protection Against Termination of Employment (PHK) by Companies Towards Breastfeeding Mothers Providing Exclusive Breastfeeding as Regulated by Presidential Regulation No. 2 Of 2022 Concerning Job Creation Aulia Ramadhan; Beni Satria; Irsyam Risdawati
UNES Law Review Vol. 6 No. 2 (2023): UNES LAW REVIEW (Desember 2023)
Publisher : LPPM Universitas Ekasakti Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31933/unesrev.v6i2.1286

Abstract

This research aims to analyze the legal protection against Termination of Employment (PHK) by companies towards breastfeeding mothers providing exclusive breastfeeding, based on Presidential Regulation No. 2 of 2022 Concerning Job Creation. The research employs a normative legal research method, examining legal regulations, doctrines, and principles relevant to the legal protection of breastfeeding mothers providing exclusive breastfeeding. In order to support the implementation of Presidential Regulation No. 2 of 2022 concerning Job Creation, there is a need for collaboration and coordination among the government, businesses, cooperatives, MSMEs, and labor force. The government must ensure that this policy is implemented fairly, taking into account workers' rights and sustainable economic empowerment. Cooperation from all relevant parties is key to achieving the goals of this structural reform in the context of the complex global economic conditions. Although Presidential Regulation No. 2 of 2022 concerning Job Creation does not specifically regulate the rights of breastfeeding workers, women workers breastfeeding at the workplace are still protected by the Labor Law. This includes the right to leave, time and facilities for breastfeeding, as well as a prohibition on termination of employment on the grounds of breastfeeding. Despite the impact of this regulation on the labor sector, it is crucial to monitor and evaluate its implementation periodically to ensure that the goals of worker protection and economic empowerment are achieved as expected.
BLDC Motor Speed Control System for Drone Applications Using Tuned PID Control by Particle Swarm Optimization (PSO) Jekli Boy Nainggolan; Beni Satria; Ahmad Dani
INFOKUM Vol. 14 No. 03 (2026): Infokum, May - June 2026
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/infokum.v14i03.3120

Abstract

This study addresses the challenge of optimal speed control for Brushless DC (BLDC) motors in drone applications, where precise and responsive control is critical for stability and maneuverability. While the Proportional-Integral-Derivative (PID) controller is standard, manual tuning for dynamic drone operations is often suboptimal. This research proposes and investigates the implementation of a PID controller whose parameters are automatically tuned using the Particle Swarm Optimization (PSO) algorithm. The primary objective is to design a superior control system that enhances transient response and robustness against disturbances common in drone flight. The methodology employs a simulation-based experimental design using MATLAB/Simulink. The PSO algorithm optimizes the PID parameters (Kp, Ki, Kd) by minimizing the Integral Time Absolute Error (ITAE) as the fitness function. The performance of the PSO-tuned PID is then compared against a conventionally tuned (Ziegler-Nichols) PID controller under scenarios including step response and load disturbance. The findings demonstrate that the PSO-PID controller significantly outperforms the conventional PID, achieving a 73% reduction in overshoot (from 14.2% to 3.8%), a 25% faster settling time, and a 28.9% quicker recovery from load disturbances. Statistical t-test analysis confirms the significant superiority of the PSO-optimized system (p < 0.001). The implications of this research are substantial, offering an efficient offline tuning method that can be deployed on flight controllers to enhance drone stability, performance, and operational reliability without requiring additional real-time computational power, thereby advancing control system design for unmanned aerial vehicles.
Development of IoT-Based MPPT System Using Perturb and Observe Algorithm on Solar Panels Irham Purba; Beni Satria; Ahmad Dani
INFOKUM Vol. 14 No. 05 (2026): Infokum, 2026
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/infokum.v14i05.3164

Abstract

This study successfully designed and implemented an IoT-based Maximum Power Point Tracking (MPPT) system using the Perturb and Observe (P&O) algorithm for a 100 Wp polycrystalline solar panel. The research aims to provide an integrated, cost-effective solution for optimizing solar energy extraction in Indonesia's tropical climate. The methods employed include mathematical modeling, system simulation in MATLAB/Simulink, and hardware implementation using an ESP32 microcontroller with sensors for voltage, current, irradiance, and temperature, integrated with the ThingSpeak IoT platform for real-time monitoring. System validation showed high accuracy with a Root Mean Square Error of 0.83 W. The hardware system achieved an average MPPT tracking efficiency of 95.36% with a response time of 2.05 seconds and power oscillation of 3.17%, contributing to a significant 24.8% increase in daily energy yield compared to a non-MPPT system. IoT performance metrics showed a data transmission success rate of 97.08%, average latency of 2.82 seconds, and system uptime of 99.12%. This integrated MPPT-IoT system offers a practical and affordable technological solution, contributing empirical baseline data for tropical conditions and supporting Indonesia's national energy transition and net-zero emission targets through improved data-driven decision-making.
Co-Authors Ahmad Dani Aulia Ramadhan Irham Purba Irsyam Risdawati Jekli Boy Nainggolan