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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) Jurnal Teknik ITS Sinergi JURNAL NASIONAL TEKNIK ELEKTRO Proceeding of the Electrical Engineering Computer Science and Informatics JAVA Journal of Electrical and Electronics Engineering JAREE (Journal on Advanced Research in Electrical Engineering) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) Sewagati Jurnal Multidisiplin Indonesia
Dimas Anton Asfani
Institut Teknologi Sepuluh Nopember
Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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The Governor Predictive Controlled Based on LSTM for Optimizing Cofiring Power Generator Operation Addien Wahyu Wiranata; Dimas Anton Asfani; Daniar Fahmi
JAREE (Journal on Advanced Research in Electrical Engineering) Vol. 1 No. 10 (2026): January
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v1i10.549

Abstract

The renewable energy with cofiring technology has a significant impact on the use of Biomass. The use of biomass with different qualities greatly affects the performance of a plant. Deep Learning Time Series Forecasting is designed for predicting two control parameters cofiring powerplant operation consist of governor control and output generator. Long Short-Term Memory (LSTM) combined with Multilayer Perceptron, Convolutional, and Adaptive Moment Estimation (ADAM) optimizer algorithms are utilized to optimize the process governor control and predict generating power output. Correlation analysis is used to determine the input variables and resulting input parameters of governor control prediction consist of Temperature Steam, Pressure Steam, Output Generator, Coal Flow, Flow Steam. Moreover, the input variable for prediction generation power output are steam flow, steam temperature, coal flow, and steam pressure. The combination of Deep Learning Forecasting is successfully to predict both operation parameter percentage errors of 5.33%.
Test Commissioning Panel LVMDP (Low Voltage Main Distribution Panel) pada Bangunan Masjid Negara Ibu Kota Nusantara Dikyi Alvian; Dimas Anton Asfani; Agus Setiono
Jurnal Multidisiplin Indonesia Vol. 4 No. 3 (2026): September: Jurnal Multidisiplin Indonesia
Publisher : PT. ALHAFI BERKAH INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62007/joumi.v4i3.964

Abstract

Masjid Negara in Nusantara Capital City (IKN) is a national strategic infrastructure designed as a Smart Building (Bangunan Gedung Cerdas / BGC), demanding high operational reliability and electrical power continuity. This engineering work aims to analyze and verify the physical, technical, and operational feasibility, digital communication integration, testing findings classification, HSE management effectiveness, engineering code of ethics compliance, and budget allocation for a 2500 A Low Voltage Main Distribution Panel (LVMDP) interconnecting the main PLN grid and a 1250 kVA Emergency Backup Generator Set. The methodology included non-energized testing of busbar insulation resistance, bolt torque verification, and grounding resistance, followed by energized testing of voltage stability, phase sequence, ATS automation simulation, and Modbus RS-485 data transmission integration into the Building Automation System (BAS). All execution stages prioritized public safety, technical integrity, professionalism, and compliance with the Construction Safety Management System (SMKK) under PUPR Ministerial Regulation No. 10/2021, achieving zero accidents. Test results confirmed busbar insulation resistance ≥1 MΩ, grounding resistance ≤2 Ω, and bolt torque compliance with mechanical specifications. No critical findings were identified, while major and minor findings were rectified. Automatic transfer times complied with NFPA 110 standards. DPM integration into BAS via Modbus RS-485 successfully provided accurate real-time electrical telemetry. Based on testing and commissioning cost analysis, the LVMDP 2500 A is declared fit for operation and compliant with PUIL 2020, IEC 61439, and PUPR Ministerial Regulation No. 21/2021.
Co-Authors Achmad Affandi Addien Wahyu Wiranata Ade Kurniawan Putra Adi Soeprijanto Affandi Afif Al Asyad Afif, Yusrizal Agus Setiono Ahmad Faiz Farizy Akbar, Muhammad Fadlan Ardyono Priyadi Arief Budi Ksatria Arwindra Rizqiawan Azmi Wicaksono Daniar Fahmi, Daniar Dedet Candra Riawan Devy Kuswidiastuti Diaz Ficry Arfianto Dicky Wahyu Darmawan Dikyi Alvian Dwi Krisna Cahyaningrum Fadhilah, Arkan Febrianto Wahyu Utomo Husnah, Nurul I Gusti Ngurah Satriyadi Hernanda I Made Yulistya Negara Imam Mukhlash Indra Sidharta Irmawati, Novia Ayu Isti Qomah Liga Primabaraka M, Arief Made Yudha Pranadiksa Giri Made Yudhi Setyawan Mochammad Wahyudi Mohammad Iqbal Mubarok, Abdul Fattah Muhammad Eko Septiawan Muhammad Sulthon Novera Rega Musthofa, Arif Neisya Islamey Rifma Nugraha, Yurid Eka Onang Surya Nugroho P, Gilang Dwi Prajanuarto, Bimo Puji Handayani Pujiantara, Margo R. Wahyudi Rajavalens, Muhammad Rifki Wiryatama Roikhana Farista Dewira Rukmana, Maman Ryan Nurdianto Setijadi, Eko Siti Sudatul Aisyah N Sitorus, Philip Nathanael Erlangga Soedibyo Soedibyo Subekti, Hakim Sudatul Aisyah N, Siti Supriyono, Joko Surya Dwi Kisdarmawan Suwadi Suwadi Suwito Suwito Titiek Suryani Tri Desmana Rachmildha, Tri Desmana Widyatama, Anton Putra Yoga Uta Nugraha Yulistya, I Made Yuniarto, Muhammad Nur Zaidan, Risyad Alauddin