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Sistem Monitoring Perilaku Pengendara Mobil Berbasis Internet of Things Rahayu, Andri Ulus
JITCE (Journal of Information Technology and Computer Engineering) Vol. 5 No. 01 (2021)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.5.01.18-24.2021

Abstract

This research is created as a system for a car rental service. The system has monitoring features allowing the car rental owner to monitor the engine condition. The monitoring is performed by using a web interface that could read data from OBD-II that sent by raspberry pi 2. The owner can also monitor the position of the car by using coordinates sent from a smartphone by utilizing the GPS feature. In addition, it also has a reporting feature that allows the owner to track the data history from OBD II about the engine rpm, speed, engine load & temperature. Moreover, the owners can identify the route that has been passed by their car. Likewise, this system provides a program that analyzes the car driver's behavior based on the determined rules. The analysis was conducted based on all data from OBD-II in the database server and all data of driving rules violation performed by the driver. The result is an assessment of the driver as a driving error rate. This study generated 173 data of which 9 were driving rules violations with a 5.20% driving error rate. The report can be obtained by selecting the time interval. It also downloadable and can be sent by e-mail.
Harmonic reduction in power grids: implementing a four-legged multilevel inverter as an active power filter using model predictive control Andang, Asep; Nursuwars, Firmansyah Maulana; Rahayu, Andri Ulus; Taufiqurrahman, Imam; Paryono, Ervan
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 2: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v16.i2.pp922-935

Abstract

This study explores the implementation of a five-level cascaded three-phase four-wire inverter as an active power filter to mitigate harmonics in power grids. Harmonic components in the load current are transformed and filtered to create a reference current, which serves as the foundation for designing the inverter’s switching pattern. The predicted current, generated through circuit modeling, is compared with the reference current using the model predictive control (MPC) method. The accuracy of this approach is evaluated using a cost function that measures the difference between the predicted and reference currents. Simulation results reveal that the application of the hybrid power filter can effectively suppress harmonics, reducing the total harmonic distortion (THD) to below 5%, thereby meeting power quality standards. Furthermore, it addresses load imbalances, ensuring that the phase currents at the source remain nearly equal. Additionally, the hybrid power filter significantly decreases the neutral current, reducing it to just one-tenth of its original value. While MPC has demonstrated its effectiveness in controlling power converters and multilevel inverters, its application to active power filters remains underexplored. This study investigates the potential of a four-legged multilevel inverter with MPC to enhance power quality by reducing harmonics in three-phase four wire systems.
An IoT-Based Framework for Real-Time Monitoring and Evaluation of Child Growth to Support Indonesia’s Stunting Reduction Initiative Andri Ulus Rahayu; Taufiqurrahman, Imam; Arie Gustaman, Rian; Fittur Farabi Sanaz
Jurnal Teknokes Vol. 18 No. 2 (2025): June
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Stunting remains a significant public health concern in Indonesia, leading to lifelong developmental and economic disadvantages. This study aims to address limitations in conventional child growth monitoring by developing and validating an IoT-based system that integrates ultrasonic and load cell sensors, an ESP32 microcontroller, RFID identification, and cloud-based data management. The system enables automated, real-time measurement and digital record-keeping, accessible via a user-friendly dashboard. Empirical validation was conducted on 35 children at local Integrated Health Service Post (Posyandu), showing high measurement accuracy (±0.53 cm for height, ±0.08 kg for weight), rapid average data transmission (2.05 seconds), and strong agreement with manual gold standards (p > 0.05). Usability evaluations indicated high satisfaction among health cadres, with streamlined workflows reducing time and staff requirements. The findings demonstrate that the proposed IoT-based system offers an effective, scalable, and economically viable solution for improving child growth monitoring and supporting stunting prevention programs in community health settings.