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All Journal Jurnal Nasional Pengelolaan Energi MigasZoom Jurnal Riset Teknologi Pencegahan Pencemaran Industri ELPOSYS: Jurnal Sistem Kelistrikan
Novan Akhiriyanto
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Chemical Engineering, Chemistry & Bioengineering Chemistry Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering

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Implementation of Integrating PV System Production Forecasting Using Recurrent Neural Networks in Local Weather Station Prototype Novan Akhiriyanto; Listianto, Setiawan; Basmana, Naufal
Jurnal Riset Teknologi Pencegahan Pencemaran Industri Vol. 16 No. 1 (2025): May
Publisher : Balai Besar Standardisasi dan Pelayanan Jasa Pencegahan Pencemaran Industri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21771/jrtppi.2025.v16.no1.p16-22

Abstract

This study explores the crucial role of weather stations in measuring, collecting, and reporting weather data, as well as the implementation of modern technologies such as Long Range (LoRa) radio wave modulation technology for real-time data monitoring. Equipped with components like temperature, humidity, solar radiation, and wind sensors, the weather station ensures accurate and efficient data collection. Testing of LoRa technology at the PEM Akamigas Campus demonstrated an effective range of approximately ±85 meters, ensuring optimal connectivity between the Subroto Building and the Energy Laboratory Building. Data consistency from the Message Queue Telemetry (MQTT) protocol server and Haiwell Human-Machine Interface (HMI) confirms the reliability of weather monitoring. Additionally, this research focuses on weather and energy production predictions for the PV system at the Subroto Building, using an Recurrent Neural Network (RNN) deep learning model to enhance the accuracy of solar panel energy production forecasts. Data evaluation from April 1, 2024, to April 22, 2024, highlights the potential. Based on the real-time sensor data installed in the field on a combination of 3 series solar panels, resulted in production forecasting with Root Mean Square Error (RMSE) values of approximately 4.9965 for voltage, and 0.0081 for current. This indicates fairly satisfactory results. For power testing, the RMSE results are still unsatisfactory, highlighting an opportunity for future model improvements. The combination of LoRa technology and the RNN model is expected to provide valuable insights into reliable weather monitoring and energy production at the PEM Akamigas Campus, with improvements to the model parameters for power data, which is inherently derived from the multiplication of voltage and current parameters.
Pemeliharaan Tahunan Pressure Transmitter Area Steam Generation Industri Petrokimia di PT. X Hafiz, Muhammad; Novan Akhiriyanto
Elposys: Jurnal Sistem Kelistrikan Vol. 12 No. 2 (2025): ELPOSYS vol. 12 no. 2 (2025)
Publisher : Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/elposys.v12i2.6424

Abstract

Monitoring steam generation systems in the petrochemical industry is essential because small pressure changes can significantly affect product quality and pose safety risks. This study focuses on calibrating the Endress+Hauser Cerabar M PMC41 pressure Transmitter at PT. X, a leading Indonesian fatty alcohol and oleochemical producer. Calibration was performed to ensure accurate pressure measurement of steam generation processes using a zero calibration technique to correct reading Errors. Measurement data were collected before and after calibration at 0%, 25%, 50%, and 100% pressure levels. The initial Error in pressure measurement was 31.799 bar (4.47%), while the current output Error was 16.76 mA (3.8%). After calibration, these Errors reduced to 30.266 bar (0.72%) and 16.023 mA (0.115%), respectively. These results indicate a significant improvement in the Transmitter’s performance, aligning with the International Electrotechnical Commission (IEC) No. 13B-23 standards. The calibration process effectively minimized measurement Errors, ensuring precise monitoring of pressure parameters in the steam generation system and maintaining operational stability. Accurate pressure control is crucial to optimizing production efficiency and maintaining safety standards at PT. X.
RANCANG BANGUN SiSTEM BATCH CONTROL AIR PENGUMPAN PADA PRODUKSI BROWN GAS BERBASIS ELEKTROLISIS ALKALI Novan Akhiriyanto; Ibrahim, Ahmad Rasyid; Adi, Wasis Waskito; Dewi, Astrie Kusuma
Jurnal Nasional Pengelolaan Energi MigasZoom Vol. 7 No. 2 (2025): Jurnal Nasional Pengelolaan Energi MigasZoom
Publisher : Pusat Pengembangan Sumber Daya Manusia Minyak dan Gas Bumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37525/mz/2025-2/1171

Abstract

Elektrolisis air merupakan proses terjadinya penguraian air menjadi gas hidrogen dengan dialiri arus listrik searah melalui elektroda katoda dan anoda yang tercelup ke dalam larutan elektrolit. Penelitian ini untuk merancang prototype batch control system pada produksi hidrogen menggunakan metode elektrolisis. Sistem dikembangkan dengan sistem otomatis untuk meningkatkan efisiensi pada produksi hidrogen, khususnya brown gas atau gas HHO, karena proses elektrolisis alkali yang belum terpisah antara gas hidrogen dan gas oksigen. Proses elektrolisis ini menggunakan larutan elektrolit Kalium Hidroksida (KOH) dengan pengaturan arus dan tegangan yang bervariatif. Terdapat komponen utama yang digunakan yaitu tabung electrolyzer, pompa DC, solenoid valve DC, level switch, mikrokontroler ESP32, sensor Electrical Conductivity (EC), dan sensor MQ-8. Untuk melakukan pengujian diperlukan database InfluxDB dan antarmuka Grafana yang mempermudah interaksi antara alat dengan manusia. Hasil yang diperoleh menunjukkan bahwa batch control system mampu beroperasi stabil, dengan keluaran hidrogen yang lebih tinggi pada kondisi tegangan suplai 6V dengan arus 8A. Namun, karena pengujian masih terbatas pada 2 kondisi ujicoba, maka kondisi terbaik hanya berlaku pada rentang percobaan yang telah dilakukan, sehingga penelitian lanjutan diperlukan untuk menetapkan parameter operasi yang benar-benar optimal.
Co-Authors Adi, Wasis Waskito Astrie Kusuma Dewi, Astrie Kusuma Basmana, Naufal Ibrahim, Ahmad Rasyid Listianto, Setiawan Muhammad Hafiz