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Sunardi, Sunardi
Universitas Ahmad Dahlan Yogyakarta
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Journal : journal of applied informatics and computing

 1 
Comparison of LSTM and Random Forest for Hydrogen Production Prediction in Alkaline Water Electrolysis Ulil Amri Ulil; Ardi Pujiyanta; Sunardi Sunardi
Journal of Applied Informatics and Computing Vol. 10 No. 4 (2026): August 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i4.13254

Abstract

Hydrogen has emerged as a promising clean energy carrier capable of supporting the transition toward sustainable energy systems. In alkaline water electrolysis systems, accurate prediction of hydrogen production is essential for improving system monitoring, operational efficiency, and future control strategies. This study aims to compare the performance of Random Forest (RF) and Long Short-Term Memory (LSTM) algorithms in predicting hydrogen production based on operational parameters of an alkaline water electrolysis system. The dataset used in this study consists of more than 100,000 operational data samples collected from laboratory-scale electrolysis experiments, including voltage, current, temperature, and hydrogen gas pressure measurements. Hydrogen production was calculated using the ideal gas law and used as the target variable for model development. Prior to model training, the dataset underwent preprocessing, including data cleaning, normalization, and train-test splitting. The predictive performance of both models was evaluated using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and coefficient of determination (R²). Experimental results show that the Random Forest model achieved superior performance with an MAE of 0.0085, RMSE of 0.0106, and R² of 0.9905, while the LSTM model obtained an MAE of 0.0302, RMSE of 0.0361, and R² of 0.7907. The findings indicate that Random Forest is more effective than LSTM in modeling the relationship between operational parameters and hydrogen production in the investigated alkaline water electrolysis system. This study demonstrates the potential of machine learning approaches for accurate hydrogen production prediction and provides insights into the suitability of different predictive models for electrolysis-based hydrogen generation systems.
Co-Authors Abd. Rasyid Syamsuri Abdul Djalil Djayali Abdul Fadlil Abdul Fadlil Abdul Fadlil Abdul Fadlil Abdul Fadlil Abdul Fadlil Abdul Hadi Achmad Dito Ahmad Azhar Kadim Ahmad Ikrom Ahmad Raditya Cahya Baswara Ahmad Syahril Mohd Nawi Aldi Bastiatul Fawait Fawait Alfian Ma’arif Alwas Muis Anggit Pamungkas Anton Yudhana Anton Yudhana Anton Yudhana Anton Yudhana Apik Rusdiarna Indra Praja Ardi Pujiyanta Ardiansyah Ardiningtias, Syifa Riski Ardiningtias Arief Setyo Nugroho Ariful Aziz Arizona Firdonsyah Asep Setyaji Aulia, Aulia Azrul Mahfurdz Azrul Mahfurdz Azrul Mahfurdz Azrul Mahfurdz Bambang Priambodo Bambang Subana Budi Santosa Deco Aprilliansyah Denis Prayogi Denis Prayogi Dewi Sahara Dewi Sahara Nasution Dewi Soyusiawaty Dewi Soyusiawaty Dian Novianti Doddy Teguh Yuwono Dwi Aryanto Dwi Aryanto Eko Aribowo Eko Handoyo Ermin Al Munawar Ermin Ermin Evrynda Widyasari Puspa Dewi Faqihuddin Al-anshori Fatma Nuraisyah, Fatma Fiftin Noviyanto Fijaya Dwi Bima Sakti Putra Fijaya Dwi Bima Sakti Putra Fijaya Dwi Bimasakti Firdonsyah, Arizona Fitriah Fitriyani Tella Fitriyanto, Rachmad Furizal Furizal Furizal Furizal Gema Kharismajati Guguh Makbul Rahmadani Fitra H. Ahmad Hartanta, Agus Jaka Sri Hartini, Sri Haryani Alamsyah Herman Herman Herman Herman Herman Herman Herman Herman Herman Yuliansyah Hernawan Aji Nugroho Heru Hermawan Hikmatyar Insani Himawan I Azmi Ibnu Muakhori Ihyak Ulumuddin Iif Alfiatul Mukaromah Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Irhash Ainur Rafiq Irwansyah Irwansyah Irwansyah Irwansyah Jafri Din Janu Prasetyo januari audrey January Audrey Joko Supriyanto Joko Triyanto Kemal Thoriq Al-Azis Khoir, Syaiful Amrial Krisna Astianingrum Lina Handayani Luh Putu Ratna Sundari Lukman Reza Lukman Reza M Murinto M. Ihya A. Elfatih Mardhiatul Ihsaniah Miftahuddin Fahmi Mirza Sutrisno Mitra Adhimukti Mohd Azriq Abd Aziz Muchamad Kurniawan Muchlas, Muchlas Muchrisal Muchrisal Muchrisal Muflih, Ghufron Zaida Muh. Hajar Akbar Muhammad Amirul Mu'min Muhammad Fauzan Gustafi Muhammad Fauzan Gustafi Muhammad Kunta Biddinika Muhammad Kunta Biddinika Muhammad Muizz Mohd Nawawi Muhammad Nashiruddin Darajat Muhammad Nur Ardhiansyah Muhammad Sabiq Dzakwan Muhammad Sabiq Dzakwan Muntiari, Novita Ranti Murinto Murinto Musri Iskandar Nasution Muzakkir Pangri Nasirudin Nasirudin Nazuki Nazuki Nia Ekawati Nia Ekawati Nugroho, Hernawan Aji Nur Makkie Perdana Kusuma Nur Ratnawati Nuril Mustofa Pahlevi, Ryan Fitrian Panggah Widiandana Pradana Ananda Raharja Priyatno Priyatno Puji Ristianto Puriyanto, Riky Dwi Rachmad Fitriyanto Rachmad Very Ananda Saputra Raja Bidin Raja Hassan Rajunaidi Rajunaidi Rani Rotul Muhima Restu Prima Yudha Restu Prima Yudha Rezki Ramdhani Ricky Irawan Putra Rifkan Firdaus Rio Dwi Listianto Rio Ikhsan Alfian Rosmini Rosmini Rudy Ansari Rudy Ansari Rusydi Umar Rusydi Umar Rusydi Umar Rusydi Umar Saberi Mawi Sahiruddin Sahiruddin Saifullah, Shoffan Salsabilla Azahra Putri Saputro, Mochammad Yulianto Andi Sarmini Sarmini Septiyawan Rosetya Wardhana Sharipah Salwa Mohamed Son Ali Akbar Sri Rahayu Astari Sri Rahayu Astari Sri Winiarti Sri Winiarti Subrata, Arsyad Cahya Sukma Aji Supriyanto Syaiful Khoir Syed Abdullah Syed Abdullah Syifa Riski Ardiningtias Syifa'ah Setya Mawarni Syifa’ah Setya Mawarni Syifa’ah Setya Mawarni Tole Sutikno Tomy Chandra Mahendra Tresna Yudha Prawira Tri Antoro Tristanti, Novi Ulil Amri Ulil Ummi Syafiqoh Virasanty Muslimah Wahyu S Aji Watra Arsadiando Wawan Darmawan Wijaya, Setiawan Ardi Wilda Rina Hasibuan Yana Mulyana Yuniarti Lestari Yuwono Fitri Widodo