Article Per Year (5 Year)
p-Index From 2021 - 2026
4.699
P-Index
This Author published in this journals
All Journal JURNAL KIMIA SAINS DAN APLIKASI IPTEK The Journal of Engineering JURNAL INTEGRASI PROSES IJEMS (Indonesian Journal of Environmental Management and Sustainability) Reka Buana : Jurnal Ilmiah Teknik Sipil dan Teknik Kimia Jurnal Rekayasa Hijau Jurnal Ilmiah Teknik Kimia Stannum : Jurnal Sains dan Terapan Kimia Darmabakti : Junal Pengabdian dan Pemberdayaan Masyarakat Equilibrium Journal of Chemical Engineering REACTOR : Journal of Research On Chemistry And Engineering Warta AKAB Jurnal Akademika Kimia Journal of Vocational Studies on Applied Research Jurnal Teknik Kimia dan Lingkungan JPM-AKA Jurnal Teknologi Kimia Mineral Indonesian Journal of Chemical Science Jurnal Akademika Kimia Jurnal Rekayasa Proses
Fikrah Dian Indrawati Sawali
Program Studi Teknik Kimia Mineral, Politeknik Industri Logam Morowali
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Physics Public Health Social Sciences Other

Published : 33 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 33 Documents
Search

 1   2   3   4 
Kinetic Modeling of Ni and Co Adsorption: A Comparative Study on Activated Zeolite Sawali, Fikrah Dian Indrawati; Afandy, Moh. Azhar
Rekayasa Hijau : Jurnal Teknologi Ramah Lingkungan Vol 10, No 1 (2026)
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/jrh.v10i1.1-11

Abstract

AbstractThe existence of heavy metals such as nickel (Ni) and cobalt (Co) can lead to environmental problems that have an immediate impact on human life, therefore it is crucial to carry out proper preventative strategies in wastewater treatment, one of the these utilizes the process of adsorption.  In the current investigation, thermally activated zeolite (ZT) by a carbonization process at a temperature of 550°C was utilized as a medium in the adsorption phase of Ni and Co from simulated wastewater with variation in a mass ratio of ZT.  Several kinetic models have been used for evaluating the kinetic parameters and mechanisms that control the adsorption process.  The outcomes received shown the adsorption process of Ni and Co by ZT followed the PSO kinetic model (R² > 0.99) with qe = 9.4877 mg.g⁻¹ and k₂ = 329.6075 g.mg⁻¹.min⁻¹ for Ni and qe = 7.3206 mg.g⁻¹ .min⁻¹ and k₂ = 127.9652 g.mg⁻¹.min⁻¹ for Co.  Based on the PSO kinetic model, it can be assumed that the adsorption process of Ni and Co by ZT is controlled by chemical interactions through ion exchange and the creation of coordination covalent bonds with active sites on the surface of the adsorbent.Keywords: Adsorption, Nickel, Cobalt, Zeolite
Isolation of Flavonoids from Walang Sangit Leaves (Eryngium Foetidum) Using Methanol and Acetone Maceration with UV–Visible Spectrophotometric Analysis Suhirman, Suhirman; Ardian, Adna Ivan; Sawali, Fikrah Dian Indrawati; Afandy, Moh Azhar
Reka Buana : Jurnal Ilmiah Teknik Sipil dan Teknik Kimia Vol 11, No 1 (2026): EDISI MARET 2026
Publisher : Universitas Tribhuwana Tunggadewi Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33366/rekabuana.v11i1.8072

Abstract

Flavonoids are natural phytonutrient compounds in plants that exhibit antioxidant properties and play a role in scavenging free radicals. Walang sangit leaves have potential as a source of flavonoids, with samples consisting of young and mature leaves obtained from Pagebangan, Ciwandan District, Cilegon City. The sample preparation stage was carried out through extraction using the maceration method. The experimental procedure involved 10 g of dried walang sangit leaves ground to 60 mesh, which were macerated using 99.95 percent methanol and 80 percent acetone solutions. The volume of methanol and acetone used was 250 mL, with maceration times of 60 and 120 minutes in an Erlenmeyer flask. At 120 minutes, the methanolic extract yielded 2.81 mg QE/g (young leaves) and 4.12 mg QE/g (mature leaves), whereas the acetone extract only reached 1.03 mg QE/g and 2.88 mg QE/g, respectively. A similar pattern was also observed at 60 minutes, with methanol producing values of 1.39 – 2.32 mg QE/g, which were higher than those obtained with acetone (0.35 –0.78 mg QE/g). The highest extraction rate constant was obtained for acetone–mature leaves (0.0124 / min) and for methanol young leaves (0.0058 / min).
Comparative Study of Machine Learning Algorithms for Cr(VI) Adsorption Optimization: A Case Study Using KOH-Activated Wood Charcoal Afandy, Moh. Azhar; Sawali, Fikrah Dian Indrawati
Equilibrium Journal of Chemical Engineering Vol 10, No 1 (2026): Volume 10, No 1 July 2026 (First Online)
Publisher : Program studi Teknik Kimia UNS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/equilibrium.v10i1.108769

Abstract

The removal of toxic Cr(VI) ions from industrial wastewater remains a pressing environmental concern due to their high mobility and carcinogenic nature. This study presents a data-driven approach for modeling and optimizing Cr(VI) adsorption onto KOH-activated wood charcoal using various machine learning (ML) algorithms. A dataset derived from batch adsorption experiments was used, involving three operational parameters: initial Cr(VI) concentration (10–50 mg/L), contact time (40–120 min), and adsorbent dose (0.5–1.5 g). Six supervised regression models such as Linear Regression, Decision Tree, Random Forest, Support Vector Machine (SVM), Gradient Boosting, and k-Nearest Neighbors (kNN) were evaluated. Model performance was assessed using the coefficient of determination (R²), root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) dan mean square error (MSE). Gradient Boosting and Decision Tree showed superior predictive accuracy, with R² values of 0.89 and 0.87, respectively. Feature importance analysis revealed initial concentration as the most influential factor, followed by contact time and adsorbent dosage. These findings highlight the potential of ML as an effective tool for predicting and optimizing adsorption processes in environmental remediation. The integration of ML methods supports efficient decision-making, particularly under constraints of limited experimental data, and aligns with digital transformation strategies in wastewater treatment.
Co-Authors Adelina, Dina Ardian, Adna Ivan Ardiansah, Ardiansah Arif Rahman Az Zahra , Clarisa Hany Clarisa Hany Az Zahra Devi Yuni Susanti Eryan Dwi Krisna Fery Setyawan Firman Aldani Hadiyatni Rita Priyantini Haeril, Haeril Hary Sulistyo Herliawan, Deden Jajang Harly Khatimah, Khusnul Lestary, Rara Ayu Lestary, Rara Ayu Mega Mustikaningrum Mega Mustikaningrum Mega Mustikaningrum Moh. Azhar Afandy Muh. Azis Albar. J Muslikhin Hidayat Mustika, Pra Cipta Buana Wahyu Mustikaningrum , Mega Mustikaningrum, Mega Mustikaningrum, Mega Nirwansyah Nita Widyastuti Pangeran, Andi Baso Pra Cipta Buana Wahyu Mustika Pra Cipta Buana Wahyu Mustika Putra, Aditya Perdana Putri, Raisya Fadilah Rara Ayu Lestary Samuel Putra Mandiri Simanullang Saputra, Aditya Tri Sediawan, Wahyudi B. Septiawan, Muhammad Ridwan Simanullang, Samuel Putra Mandiri SUHIRMAN SUHIRMAN Susanti, Devi Y. Wahyudi B. Sediawan Wahyudi Budi Sediawan Yudi Siswanto