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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmu Dasar SAINSMAT IPTEK Journal of Proceedings Series KONSELI: Jurnal Bimbingan dan Konseling (E-Journal) Journal of Regional and City Planning Jurnal Informatika dan Teknik Elektro Terapan Sistemasi: Jurnal Sistem Informasi Journal of Applied Geospatial Information Sinkron : Jurnal dan Penelitian Teknik Informatika RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JURNAL MEDIA INFORMATIKA BUDIDARMA JTERA (Jurnal Teknologi Rekayasa) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Unisda Journal of Mathematics and Computer Science (UJMC) Jurnal Penelitian dan Pengembangan Pelayanan Kesehatan International Journal of Pedagogy and Teacher Education J Statistika : Jurnal Ilmiah Teori Dan Aplikasi Statistika METIK JURNAL Building of Informatics, Technology and Science Jurnal Perencanaan Pembangunan Journal of Education and Learning Mathematics Research (JELMaR) International Journal of Advances in Data and Information Systems Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Layanan Masyarakat (Journal of Public Service) TheJournalish: Social and Government BERNAS: Jurnal Pengabdian Kepada Masyarakat The Journal of Indonesia Sustainable Development Planning (JISDeP) JoMMiT : Jurnal Multi Media dan IT Jurnal Riset Ilmu Ekonomi Jurnal Algoritma East Java Economic Journal Jurnal Mahasiswa Ilmu Komputer PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Journal of Multiscale Materials Informatics Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam
Harun Al Azies
Universitas Dian Nuswantoro
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INTEGRATION OF ENSEMBLE STACKING IN MACHINE LEARNING FOR THERMAL STABILITY PREDICTION OF METAL-ORGANIC FRAMEWORKS (MOF) Ananta Surya Pratama; Muhammad Diva Irnanda; Taufiqul Umam; Dandy Prasetyo Nugroho; Harun Al Azies
SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam Vol. 14 No. 2 (2025): Volume 14 Nomor 2 (September 2025)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat142759682025

Abstract

Metal–Organic Frameworks (MOF) are porous materials with broad potential in energy, catalysis, and gas storage applications; however, their thermal stability remains a critical challenge. This study aims to develop a predictive model for the thermal stability of Zn-MOF based on the Quantitative Structure–Property Relationship (QSPR) using a stacking ensemble regression approach. The model was constructed with six base algorithms—Gaussian Process, KNN Regression, Ridge Regression, Linear Regression, Lasso Regression, and Support Vector Regression (SVR)—which were subsequently combined through TheilSen Regression as a meta-learner. The evaluation results demonstrate excellent predictive performance, with an MAE of 0.0022, an RMSE of 0.0023, and an R² of 0.9994 on the test set. Validation against experimental data also revealed only a tiny prediction error, confirming the model’s ability to accurately represent the complex relationships between structural descriptors and thermal stability. Compared to single regression models, the stacking approach proved to be more stable, robust against outliers, and adaptive to heterogeneous data distributions. These findings highlight the potential of stacking ensembles as an efficient data-driven material design strategy, enabling faster identification and design of thermally stable MOF while reducing reliance on costly and time-consuming laboratory experiments.
A Robust Voting Ensemble Framework for Predicting Thermal Stability in Zn-Based Metal–Organic Frameworks Umam, Taufiqul; Al Azies, Harun; Akrom, Muhamad; Surya Pratama, Ananta; Diva Irnanda, Muhammad
Journal of Applied Informatics and Computing Vol. 10 No. 3 (2026): June 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i3.12748

Abstract

The prediction of thermal stability (TS) in zinc-based metal–organic frameworks (Zn-MOFs) is often challenged by experimental cost and distributional heterogeneity in materials datasets. This study proposes a median-based robust voting ensemble to model the TS of 151 Zn-MOF samples using four structural descriptors, nN, nZn, Het, and Lig. The framework integrates five robust linear estimators and is benchmarked against a linear kernel Support Vector Regression (SVR) model to evaluate predictive stability and generalization performance. The proposed ensemble demonstrates superior test performance (R² = 0.9986; RMSE = 0.0023) compared to SVR (R² = 0.9492; RMSE = 0.0213), indicating enhanced robustness under heterogeneous data conditions. Feature importance analysis identifies nitrogen coordination density and heteroatomic environment as the dominant contributors to TS prediction, while zinc center quantity and ligand topology exhibit comparatively minor influence. These findings confirm that median-based robust aggregation improves predictive reliability and provides chemically interpretable insight, offering a data-driven approach for the rational design and screening of thermally stable Zn-MOF materials.
Co-Authors Achmad Wahid Kurniawan Achmad Wahid Kurniawan Adhitya Nugraha Agus Suharsono Alfa Trisnapradika, Gustina Alzami, Farrikh Ananda, Imanuel Khrisna Ananta Surya Pratama Andrean, Muhammad Niko Annisa Himatul Chasanah Anwar Efendi Nasution Aprilyani Nur Safitri Ardytha Luthfiarta Ariyanto, Noval Ayu Febriana Dwi Rositawati Ayu Pertiwi Ayu Pertiwi Bambang Widjanarko Otok Brilianti Rochmanto, Hani Brilianto, Rivaldo Mersis Budi, Setyo Chasanah, Annisa Himatul Dandy Prasetyo Nugroho De Rosal Ignatius Moses Setiadi Dea Trishnanti Dea Trishnanti Devi Putri Isnarwaty Dewi Agustini Santoso Dikaputra, Ishak Bintang Diva Irnanda, Muhammad Elvira Mustikawati P.H Fahmi Amiq Farrikh Al Zami Fatma Ahardika Nurfaizal Fawwaz Atha Rohmatullah Firmansyah, Gustian Angga Fitriani, Fenny Gangga Anuraga Ganiswari, Syuhra Putri Go, Agnestia Agustine Djoenaidi Guruh Fajar Shidik Gustina Alfa Trisnapradika Hani Brilianti Rochmanto Herawati, Wise Herowati, Wise Hidayat, Novianto Hidayat, Novianto Nur Ifan Rizqa Ika Puspitasari Indah Putianik Irnanda, Muhammad Diva Ishak Bintang Dikaputra Isnarwaty, Devi Putri ISWAHYUDI ISWAHYUDI Junta Zeniarja Kharisma, Ni Made Kirei Maulana, Isa Iant Megantara, Rama Aria Moch Anjas Aprihartha Mohammad Arif Muhamad Akrom Muhamad Akrom Muhammad Diva Irnanda Muhammad Naufal Muhammad Naufal, Muhammad Muljono Muljono Naufal Malik Herlambang Noor Ageng Setiyanto, Noor Ageng Noval Ariyanto Novianto Hidayat Nugraini, Siti Hadiati Nugroho, Dandy Prasetyo Nur Safitri, Aprilyani Prabowo, Wahyu Aji Eko Pratama, Ananta Surya Pravesti, Cindy Asli Pulung Nurtantio Andono Purhadi Purhadi Putra, Permana Langgeng Wicaksono Ellwid Rahman, Irfan Fauzia Rahmawati Erma Standsyah Ramadhan Rakhmat Sani Riadi, Muhammad Fatah Abiyyu Ricardus Anggi Pramunendar Rivaldo Mersis Brilianto Rohmatullah, Fawwaz Atha Ruri Suko Basuki Safitri, Aprilyani Nur Sari Ayu Wulandari Setyo Budi Shafwah, Shifatush Shifatush Shafwah Sofiani, Hilda Ayu Sri Winarno Sri Winarno Sudibyo, Usman Supriadi Rustad Surya Pratama, Ananta T. Sutojo Taufiqul Umam Trishnanti, Dea Trisnapradika, Gustina Alfa Umam, Taufiqul Usman Sudibyo Vivi Mentari Dewi Wachid Zufar Ramadhan Wahyu Aji Eko Prabowo Wahyu Wisnu Wardana Wise Herawati Wise Herowati Zahro, Azzula Cerliana Zain, Affa Fahmi Zami, Farrikh Al