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Journal : Journal of Applied Smart Electrical Network and System (JASENS)

Sistem Input Output Inventaris Tools Menggunakan Long Range RFID Study Case di PLTA Sutami Fa'iz, Muhammad; Joko Endrasmono; Sholahuddin Muhammad Irsyad; Lilik Subiyanto; Anggar Juna Puncak Pujiputra; Mustika Kurnia Mayangsari
Journal of Applied Smart Electrical Network and Systems Vol 6 No 01 (2025): Vol 06, No. 01 June 2025
Publisher : Indonesian Society of Applied Science (ISAS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/jasens.v6i01.1152

Abstract

The problem faced by Sutami Hydroelectric Power Plant in the management and data collection of tools is that the data collection is still done manually, and some tools are not returned to their place due to negligence in use. To support the achievement of the 5S culture (Seiri, Seiton, Seiso, Seiketsu, Shitsuke) at Sutami Hydroelectric Power Plant, an automated tools management system is needed. In the application of the goods input and output system, many are still using low frequency RFID with a reading range of >5cm so that tapping must be done with an RFID Reader. This still has the potential for an unrecorded loan process if the item is not tapped. This research optimizes the tools management system with long range RFID. With the designed update, it is expected that the tools management system at Sutami Hydroelectric Power Plant can provide increased productivity and also achieve the 5S culture at Sutami Hydroelectric Power Plant.
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.
Koordinasi Rele Arus Lebih di Perusahaan Nikel Indonesia Menggunakan Grasshopper Optimization Algorithm Putra, Riko Satrya Fajar Jaelani; Aulia Rahma Annisa; Yudi Andika; Sholahuddin Muhammad Irsyad; Rahmat Basya Shahrys Tsany
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/kn1tk933

Abstract

Setiap sistem kelistrikan bergantung pada ketersediaan energi yang berkelanjutan untuk menjaga produktivitas industri tetap berjalan. Gangguan listrik akan merusak peralatan listrik. Sistem proteksi berfungsi untuk meminimalkan hingga menghilangkan gangguan secara cepat, selektif, dan terkoordinasi demi meminimalkan kerusakan sistem dan memastikan pasokan listrik yang tidak terputus. Khususnya untuk rele arus lebih, time dial setting (TDS) merupakan aspek penting yang harus dipertimbangkan perihal koordinasi proteksi. TDS mengatur waktu operasi rele untuk mengamankan sistem kelistrikan. Umumnya, perhitungan manual digunakan untuk menentukan nilai TDS. Metode trial and error sering digunakan untuk mengoordinasikan rele satu sama lain. Metode ini telah berkembang menjadi algoritma cerdas yang dapat menemukan solusi secara efektif dan cepat, salah satu algoritmanya adalah grasshopper optimization algorithm (GOA). Hasil dari simulasi pada penelitian ini didapatkan nilai koordinasi antara rele 4 bekerja pada 0,1 detik & rele 3 bekerja pada 0,3 detik saat timbul gangguan pada trafo 2, rele 3 bekerja pada 0,297 detik & rele 2 bekerja pada 0,496 detik saat timbul arus gangguan pada bus 4, rele 2 bekerja pada 0,492 detik & rele 1 bekerja pada 0,493 saat timbul arus gangguan pada bus 3 serta kinerja rele 1 yang hanya sebagai primer untuk mengamankan generator bekerja pada 0,354 detik saat timbul arus gangguan pada bus 2 telah menghasilkan nilai perhitungan TDS yang akurat serta masih mematuhi aturan pengaturan minimum nilai coordination time interval (CTI) antara rele primer dan rele backup yaitu 0,2 detik dalam satu rating tegangan dan mendekati 0 di rating tegangan yang berbeda.