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Arif Afandi
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FRONTIER ENERGY SYSTEM AND POWER ENGINEERING Electrical Engineering, Universitas Negeri Malang Jl. Semarang 5, Malang 65145, Jawa Timur, Indonesia
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Kota malang,
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INDONESIA
Frontier Energy System and Power Engineering
Published by Universitas Negeri Malang
ISSN : -     EISSN : 27209598     DOI : http://dx.doi.org/10.17977/um049v2i1p1-6
Core Subject : Science, Engineering,
Control & Systems Engineering Electrical & Electronics Engineering Energy
Frontier Energy System and Power Engineering, FESPE, is an International Journal registered at e-ISSN: 2720-9598. FESPE is officially published by Electrical Engineering, State University of Malang, Indonesia. This journal is the Peer Review and Open Access International Journal, published twice a year in January and July relating to the broad scope of the Energy System and Power Engineering. FESPE provides a flagship forum for academics, researchers, industry professionals, engineers, consultants, managers, educators, and policymakers who work in engineering to contribute and disseminate new innovative works in energy systems, power engineering, and other related themes.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 5 Documents
 1 
Search results for , issue "Vol 5, No 1 (2023): January" : 5 Documents clear
Gated Recurrent Unit (GRU) for Forecasting Hourly Energy Fluctuations Aji Prasetya Wibawa; Alfiansyah Putra Pertama Triono; Andien Khansa’a Iffat Paramarta; Faradini Usha Setyaputri; Ade Kurnia Ganesh Akbari; Akhmad Fanny Fadhilla; Agung Bella Putra Utama; Leonel Hernandez
Frontier Energy System and Power Engineering Vol 5, No 1 (2023): January
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um049v5i1p16-25

Abstract

In the current digital era, energy use undeniably supports economic growth, increases social welfare, and encourages technological progress. Energy-related information is often presented in complex time series data, such as energy consumption data per hour or in seasonal patterns. Deep learning models are used to analyze the data. The right choice of normalization method has great potential to improve the performance of deep learning models significantly. Deep learning models generally use several normalization methods, including min-max and z-score. In this research, the deep learning model chosen is Gated Recurrent Unit (GRU) because the computational load on GRU is lighter, so it doesn't require too much memory. In addition, the GRU data is easier to train, so that it can save training time. This research phase adopts the CRISP-DM methodology in data mining as a solution commonly used in business and research. This methodology involves six stages: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. In this research, the model was obtained using five attribute selection, which applied 2 normalization methods: min-max and z-score. With this normalization, the GRU model produces the best MAPE of 3.9331%, RMSE of 0.9022, and R2 of 0.9022. However, when using z-score normalization, the model performance decreases with MAPE of 10.4332%, RMSE of 0.7602, and R2 of 0.4213. Overall, min-max normalization provides better performance in multivariate time series data analysis.
Implementation of Backpropagation Artificial Neural Network for Electricity Load Forecasting in Jember District Eko Pambagyo Setyobudi; Ilham Ari Elbaith Zaeni
Frontier Energy System and Power Engineering Vol 5, No 1 (2023): January
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um049v5i1p26-31

Abstract

The increase in population and various kinds of human activities in the world has made it possible for changes to increase the need for electrical power with demand that is not the same at any time. Based on this description, this research will propose research on the theme of electricity load forecasting as a preventive measure to determine future electricity load needs. Research was assisted using MATLAB data processing software to process research data. Three forecasting models were carried out, namely day, night and day-night conditions. From these three forecasting models, parameters such as epoch, number of input layers, number of hidden layers, activation function, and etc. The data is divided into two parts, training data and test data with a ratio of 70: 30. Test results using the backpropagation artificial neural network method show the highest MSE values for the three forecasting models, day, night, and day-night, are, 0.0039, 0.0041, and 0.002 while the lowest MSE values were in the three models are, 6.77E-04, 0.001, and 0.0011.
Implementation of Mamdani Fuzzy Logic on PLN Electricity Sales in East Java Muhammad Hafiizh; Muchamad Wahyu Prasetyo; Aripriharta Aripriharta; Anik Nur Handayani
Frontier Energy System and Power Engineering Vol 5, No 1 (2023): January
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um049v5i1p32-40

Abstract

This research aims to provide innovation in the development of a smarter and more adaptive electricity distribution system, able to face the challenges that arise in the digital era. The results of this research can be a guide in improving the efficiency and reliability of electricity sales. The experimental method is applied by implementing mamdani fuzzy logic on PLN electricity sales data in East Java. From the results of the application of mamdani fuzzy by comparing the prediction results with the original data, the Mean Absolute Error (MAE) result is 0.17% and the Root Mean Squared Error (RMSE) value is 0.21%. So it can be concluded that fuzzy logic mamdani method can be used in predicting electricity sold and provide valuable guidance for PLN in improving the efficiency and reliability of electricity sales in the East Java region in a sustainable manner.
Analysis of Efforts to Overcome Voltage Drops by Installing Substations in Low Voltage Networks with ETAP Simulation IG Suputra Widharma; IN Sunaya; IGN Sangka; IM Sajayasa; IKG Sri Budarsa
Frontier Energy System and Power Engineering Vol 5, No 1 (2023): January
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um049v5i1p01-08

Abstract

Electric power is an energy of secondary that generated, transmitted and distributed to consumers and used to many activities. Electrical power system is electrical power installation system is consists of generation system, transmitting system, and distribution system that integration and function to supply electric power consumption. For this purpose, both of quantity and quality also continuity in PT PLN wished can be provides and distributes electric power to consumers and all of people. One of the main materials of the distribution network to distribute electric power to customers is the distribution substation in which there is a transformer. Transformer as a means of distribution of electrical energy is susceptible to interference. Distribution substation SM 0075 Feeder Bajera is one of the distribution substations that experienced a voltage drop at the end of the JTR in the C direction. So, to fix the problems that occurred, PT. PLN has added a substation. With the addition of substations, it is necessary to pay attention to the power losses that arise, not to cause greater power losses. Based on the results of the calculations at the distribution substation SM0075 Bajera feeder before and after the addition of the insertion substation, it was found that the voltage drop at the end of the JTR direction C at the SM0075 distribution substation was 22.638% in the R phase, 15.745% in the S phase and 14.005% in the T phase. the result of the addition of the substation is a smaller power loss with the difference before and after that is equal to 2739.986472 Watt. then viewed from the quality of the voltage and environmental conditions, the C18D6A1D3 pole is better for insertion substations than the C18D6A1D2 pole based on the Etap 12.6 simulation.
Comparative Analysis of External Lightning Protection Systems Using Protective Angle and Rolling Sphere Method in Areas That Have High Lightning Intensity Gilang Indrianto Pramono; Mohamad Rodhi Faiz; Langlang Gumilar; Sujito Sujito
Frontier Energy System and Power Engineering Vol 5, No 1 (2023): January
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um049v5i1p09-15

Abstract

Indonesia is a tropical country with a geographical condition where 71% of its area is water. This is what coueses Indonesia is considered a country with a high density of lightning strikes. This results in buildings in Indonesia being at a high risk of damage caused by lightning strikes. According to data from BMKG, the city of Malang has a high lightning intensity, with 108 thunderstorm days per year, posing a serious threat to the Electrical Engineering Building of the Faculty of Engineering at the University of Malang. Considering the building's age and expansion on the building's side, it is necessary to evaluate the lightning protection system to determine whether the existing system is still working effectively and efficiently. Improving the system's performance against lightning disturbances can be done by analyzing the previous external lightning protection system and then evaluating it using the angle of protection and rolling sphere methods. The analysis and evaluation of the external protection system are based on PUIPP, PUIL, SNI, and IEEE standards.

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