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All Journal IRA Jurnal Teknik Mesin dan Aplikasinya (IRAJTMA) JURUTERA (Jurnal Umum Teknik Terapan) Advance Sustainable Science, Engineering and Technology (ASSET)
Rifki Hermana
Universitas Persatuan Guru Republik Indonesia Semarang
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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Design and Performance Evaluation of an IoT-Based Teleoperated Shuttlecock Launcher for Dynamic Badminton Training Muchamad Malik; Agus Mukhtar; Aan Burhanuddin; Rifki Hermana; Ibnu Toto Husodo; Dwi Yan Damar Arya Prananta; Subkhan Ma'mun
JURUTERA - Jurnal Umum Teknik Terapan Vol 13 No 01 (2026)
Publisher : Fakultas Teknik Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55377/jurutera.v13i01.14699

Abstract

Advanced badminton training requires dynamic attack simulations that are difficult to fulfill by human coaches or conventional static machines. This study aims to design, implement, and evaluate the performance of an interactive shuttlecock launcher prototype based on the Internet of Things using wireless remote control. The research method uses a quantitative experimental approach through research and development focused on mechanical actuation precision and network transmission reliability. Evaluations were conducted by measuring projectile launch speed and landing accuracy across six random court zones. The results showed a highly proportional mechanical precision with a maximum launch speed reaching three hundred and eight point five kilometers per hour. Spatial accuracy testing resulted in a mean absolute error of zero point twenty-two meters, which is technically advantageous as it simulates the uncertainty of human strokes due to aerodynamic drag. Network performance demonstrated an end-to-end latency of forty-five milliseconds and a data packet loss of zero point four percent, well below the human visual perception threshold of two hundred milliseconds. In conclusion, this system is proven to be highly responsive and capable of transforming a static launcher into a robotic extension for coaches, allowing instant manipulation of speed and direction to train athletes' anticipatory agility in real match conditions.
Hybrid XGBoost-LSTM Framework for Accurate SOC, SOH, DOD and Internal Resistance Estimation in Li-ion Cells Axel Putra Pralano; Florence Gnana Poovathy John; Rifki Hermana
Advance Sustainable Science Engineering and Technology Vol. 8 No. 2 (2026): February-April
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i2.3119

Abstract

Accurate estimation of State of Charge (SOC), State of Health (SOH), Depth of Discharge (DOD), and internal resistance is critical for Battery Management Systems (BMS) in electric vehicles and energy storage. Conventional methods fail to capture the nonlinear and temporal dynamics of lithium-ion cells, while existing machine learning approaches lack systematic benchmarking for embedded deployment. This study evaluates three hybrid models XGBoost-LSTM, XGBoost-SVR, and Linear Regression-Random Forest on high-resolution Samsung 30T single-cell data (five cycles, 6,081 timesteps). Models used 35 mutual information-selected features, identical preprocessing, and Bayesian hyperparameter optimization. XGBoost-LSTM achieved superior accuracy: SOC (R²=0.983), SOH (R²=0.985), DOD (R²=0.977), and internal resistance (R²=0.972), outperforming baselines significantly (Wilcoxon p<0.05). Computational profiling showed 15 ms inference latency and 60 MB memory usage, suitable for real-time BMS at 10 Hz. Results indicate that hybrid temporal learning improves battery diagnostics, while further validation across multiple chemistries, extended temperatures, multi-cell setups, and longer cycles is recommended for practical deployment.
Desain Logika Fuzzy untuk Penilaian Kualitas Air Sumur Berdasarkan Parameter Salinitas, pH, dan Kekeruhan Aan Burhanuddin; Agus Mukhtar; Rifki Hermana; Muhammad Amirudin; Muchamad Malik; Althesa Androva; Hisyam Ma’mun; Mohammad Fadillah; Ezze Zhain Zhiqqi Prihantono; Subkhan Ma'mum
IRA Jurnal Teknik Mesin dan Aplikasinya (IRAJTMA) Vol 4 No 3 (2025): Desember
Publisher : CV. IRA PUBLISHING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56862/irajtma.v4i3.333

Abstract

This study develops an integrated fuzzy-logic-based assessment system to evaluate well water quality using pH, salinity (via TDS conversion), and turbidity. The research aims to develop an adaptive system capable of handling uncertainties in water quality parameters in real-time monitoring across Semarang's coastal areas. The methodology incorporates sensor performance validation, fuzzy input processing, rule-based inference, and defuzzification implemented through MATLAB R2021a. Experimental results demonstrate exceptional metrological performance, with sensor linearity achieving determination coefficients (R²) of 0.9995 for pH, 0.9998 for salinity, 0.9996 for temperature, and 0.9993 for turbidity. Statistical validation confirmed measurement precision, with root-mean-square errors (RMSEs) of 0.018 pH units, 0.023 ppt salinity, 0.14°C temperature, and 0.027 NTU turbidity. Field implementation across 6 sub-districts revealed that 83.3% of samples complied with pH quality standards, 60% met turbidity thresholds, while 33.3% of samples in Genuksari exhibited seawater intrusion indicators with salinity levels exceeding 0.5 ppt. The study conclusively demonstrates that the developed fuzzy logic system provides accurate, consistent water quality evaluation and presents a viable framework for smart water monitoring infrastructure in coastal urban environments, particularly for detecting saline intrusion and maintaining water security.
Co-Authors Aan Burhanuddin Agus Mukhtar Althesa Androva Axel Putra Pralano Burhanuddin, Aan Dwi Yan Damar Arya Prananta Ezze Zhain Zhiqqi Prihantono Florence Gnana Poovathy John Hisyam Ma’mun Ibnu Toto Husodo Mohammad Fadillah Muchamad Malik Muhammad Amirudin Subkhan Ma'mum Subkhan Ma'mun