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All Journal Infotekmesin Journal of Applied Smart Electrical Network and System (JASENS)
Sasmita Aji Pambudi, Dwi
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Mechanical Engineering

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Kajian Eksperimen Pengaruh Variasi Perubahan Sudut Kincir terhadap Kinerja Paddle Wheel Aerator Mustaghfirin, Anis; Novianarenti, Eky; Abid Al Fatih, Muhammad; Nugroho, Priyambodo Nur Ardi; Sasmita Aji Pambudi, Dwi; Arum Wulandari, Dyah
Infotekmesin Vol 14 No 1 (2023): Infotekmesin: Januari, 2023
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v14i1.1652

Abstract

The main problem discussed in this study is the effort to improve the quality of shrimp pond water, especially the low dissolved oxygen levels by modifying the angle of the aerator wheel. The results showed that dissolved oxygen (DO) levels were very important in shrimp pond culture and that the paddle wheel aerator was a useful tool in intensive aquaculture systems because it could produce DO as needed. The study used a model designed using Solidworks software and tested at a scale of 1:10 with 3 variations of angles (15°, 35°, and 55°) at each wheel angle. The test results show that the angle variation affects the rotational speed and DO production, with the highest rotational speed and DO production achieved at an angle variation of 55°. However, the best parameters for the aerator were found at a variation of the wheel angle of 35° and a rotational speed of 300 rpm, because it produced the highest dissolved oxygen with relatively low power.
Analisis Kinerja Sistem Kontrol Hybrid Electric Vehicle (HEV) Menggunakan Metode Neuro-fuzzy Rahma Annisa, Aulia; Andika, Yudi; Muhammad Irsyad, Sholahuddin; Sasmita Aji Pambudi, Dwi
Journal of Applied Smart Electrical Network and Systems Vol. 6 No. 2 (2025): Vol. 6 No. 02 (2025): Vol 06, No. 02 Desember 2025
Publisher : Indonesian Society of Applied Science (ISAS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/f5y40s25

Abstract

Electric cars are an environmentally friendly vehicle alternative developed to reduce exhaust gas emissions and air pollution. One example is the Hybrid Electric Vehicle (HEV), which combines an Internal Combustion Engine (ICE) and an electric motor (DC motor) to improve efficiency and torque performance. HEVs generally have a smaller capacity compared to conventional vehicles, making them more fuel-efficient and energy-efficient. The system in an HEV is complex and nonlinear, requiring dynamic model approaches and appropriate control methods to maintain optimal performance. This research aims to analyze the performance of the inverse model neuro-fuzzy control system predictor implemented on an HEV. The test results show that applying a neuro-fuzzy controller can significantly improve the system's ability to achieve a response that matches the reference model. The performance of the DC motor is able to help reduce the speed error difference by up to 50 rpm with a Root Mean Square Error (RMSE) value of 0.582%. Additionally, there is a 1.411% decrease in error value compared to when the ICE is operating without using a neuro-fuzzy controller. Based on these results, the neuro-fuzzy method has proven effective in improving the accuracy and stability of the control system in HEVs.
Co-Authors Abid Al Fatih, Muhammad Arum Wulandari, Dyah Eky Novianarenti Mustaghfirin, Anis Nugroho, Priyambodo Nur Ardi Rahma Annisa, Aulia Sholahuddin Muhammad Irsyad Yudi Andika