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All Journal Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Ilmiah Teknik Elektro
Harry Ramza
Universitas Muhammadiyah Prof Dr Hamka
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy

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Penentuan Konstanta PID Sistem Kendali Satelit Sumbu X, Y, dan Z Menggunakan Metode Root Locus Muhammad Bahtiar; Mohammad Aji Saputra; Aditya Dwi Airlangga; Suraduita Mupasanta; Muhammad Mujirudin; Harry Ramza; Latifah Sarah Supian
Jetri : Jurnal Ilmiah Teknik Elektro Jetri, Volume 20, Nomor 1, Agustus 2022
Publisher : Website

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (423.366 KB) | DOI: 10.25105/jetri.v20i1.13473

Abstract

The sattelite controller can be carried out according to the orbit direction of the x, y and z axes. This control functions by determining the value of the PID constant (Proportional, Integral and Differential) through the Root Locus Method. The purpose of this study is to determine the parameters are needed by PID in controlling the LAPAN A2 Satellite using this Root Locus method. The result of P – constant on the x-axis is 31.7692, the y-axis is 38.4987 and the z-axis is 30.6559. The I – constant generated on the x-axis is 5, the y-axis is 5 and the z-axis is 5. Likewise, the D – constant generated on the x-axis is 47.2755, the y-axis is 70.2532 and the z-axis is 43.9196. All the constant values ​​mentioned are determined based on the lowest steady state error number of 0.12% for the x-axis, 0.10% for the y-axis and 0.12% for the z-axis. The overall value is the optimum system value where the steady state error value is generated from the difference between the settling time value and the steady state value multiplied by 100% with a tolerance limit of <5%.
Optimization of Energy Consumption in 5G Networks Using Learning Algorithms in Reinforcement Learning Daffa Dean Naufal; Harry Ramza; Emilia Roza
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 3 No. 2 (2023): MALCOM October 2023
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v3i2.959

Abstract

The 5G network is an evolution of the 4G LTE (Long Term Evolution) fast internet network that is widely adopted in smart phones or gadgets. 5G networks offer faster wireless internet for various purposes. This research is a literature review of several articles related to machine learning, specifically regarding energy consumption optimization with 5G networks and reinforcement learning algorithms.The results show that various techniques have evolved to overcome the complexity of large energy intake including integration with 5G networks and algorithms have been completed by many researchers. Related to electricity consumption, it was found that during 5G use cases, in a low site visitor load scenario and while reducing power intake takes precedence over QoS, power savings can be made by 80% with 50 ms latency, 75% with 20 ms and 10 ms latency, and 20% with 1 ms latency. If QoS is prioritized, then power savings reach a maximum of five percent with minimum impact in terms of latency. Moreover, with regards to power performance, it has been observed that DQN-assisted motion can offer improvements.
Co-Authors Aditya Dwi Airlangga Daffa Dean Naufal Emilia Roza Latifah Sarah Supian Mohammad Aji Saputra Muhammad Bahtiar Muhammad Mujirudin Suraduita Mupasanta