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All Journal EduChemia: Jurnal Kimia dan Pendidikan Molecular and Cellular Biomedical Sciences (MCBS) Syntax Literate: Jurnal Ilmiah Indonesia Indonesian Journal of Chemistry Eksakta : Berkala Ilmiah Bidang MIPA Journal of Materials Exploration and Findings
Fatriansyah, Jaka Fajar
Department Of Metallurgical And Materials Engineering, Faculty Of Engineering, Universitas Indonesia, Kampus Depok, West Java 16424, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Dentistry Education Energy Engineering Environmental Science Immunology & microbiology Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Social Sciences Other

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Perancangan Program Pengestimasi Probabilitas Kegagalan Peralatan Penukar Panas Akibat Korosi Seragam Berbasis Deep Neural Network Fatriansyah, Jaka Fajar; Dhaneswara, Donanta; Hanifa, Muthia; Hartoyo, Fernanda; Pradana, Agrin Febrian; Anis, Muhammad; Fauzi, Andrian
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (345.943 KB) | DOI: 10.36418/syntax-literate.v8i3.11486

Abstract

Meningkatnya standar keamanan dan ketatnya persaingan antar perusahaan meningkatkan kebutuhan bagi suatu perusahan untuk mengendalikan kegagalan pada peralatan. Inspeksi secara teratur dilakukan sebagai bagian dari rangkaian pemeliharaan dan manajemen integritas peralatan. Dalam merencanakan dan melakukan inspeksi, diperlukan strategi yang tepat agar inspeksi yang dilakukan tepat sasaran dan sesuai dengan kebutuhan. Risk-based inspection merupakan teknik pengambilan keputusan dalam perencanaan pemeliharaan yang berdasar pada risiko. Pada saat ini, penggunaan metode-metode kecerdasan buatan untuk kegiatan penilaian risiko, pemodelan konsekuensi, dan perencanaan pemeliharaan telah dilakukan. Penelitian ini bertujuan untuk mengembangkan suatu program yang memanfaatkan pembelajaran mesin dan kecerdasan buatan untuk melakukan penilaian salah satu komponen risiko yaitu probabilitas kegagalan (Probability of Failure, PoF) pada bagian cangkang dalam peralatan penukar panas menggunakan deep learning. Model ini dapat membantu operator yang bekerja di bidang minyak dan gas untuk menentukan tingkatan risiko sehingga inspeksi dapat dilakukan dengan lebih efisien dan terarah. Penelitian ini menghasilkan sebuah program dan disain program pembelajaran mesin berbasis deep learning yang digunakan untuk memprediksi risiko kegagalan akibat korosi seragam pada peralatan sisi dalam cangkang peralatan penukar panas cangkang dan buluh (shell-and-tube heat exchanger) berdasarkan standar API 581 dengan akurasi sebesar 89% yang didapatkan dengan parameter-parameter diantaranya learning rate sebesar 0.001, epoch sebesar 150, random state sebesar 60, tiga hidden layer, dan test size sebesar 0.2.
Analysis Risk Based Inspection API 581 on LPG Spherical Tank at PT. XYZ Trahmawan, Sigit; Siradj, Eddy Sumarno; Fatriansyah, Jaka Fajar
Journal of Materials Exploration and Findings Vol. 3, No. 2
Publisher : UI Scholars Hub

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Abstract

Liquified petroleum gas (LPG) spherical tanks are pressure vessel equipment for storing fuel gas products. The high pressure along with the fuel gas inside as flammable and combustible substance means that this equipment might result major accident hazard such as explosion, fires and environmental pollution. This study is aimed calculated and mitigate risk on 500 metric ton capacity LPG spherical tank using Risk-based inspection (RBI) analysis method that makes risk as its foundation. This RBI method uses quantitative analysis referring to API 581 to determine the risk of LPG Spherical Tank by determining the probability of failure (PoF) and the consequences of failure (CoF). From the results of the risk assessment will be determined appropriate methods and scheduling inspection for LPG spherical tank. As result, thinning defect mechanism is one that influences the possibility of failure of LPG ball tank equipment with a failure rate of 4.13 E-06 failure/year. The result risk assessment of LPG ball tank is at the medium-high risk level with the probability of failure being in category 1 (low) and the consequence of failure being in category E (high). Meanwhile, the recommended inspection method for LPG tank is internal and external inspection in the form of visual examination and ultrasonic thickness measurement with an inspection interval every 5 (five) years.
A Comparative Study of Conventional and Statistically Active Corrosion Methods for Corrosion Growth Assessment of a 24-inch Gas Pipeline Rinaldi, Rudi; Fatriansyah, Jaka Fajar
Journal of Materials Exploration and Findings Vol. 3, No. 3
Publisher : UI Scholars Hub

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Abstract

Component failures in oil and gas pipelines can have fatal consequences, leading to operational downtimes and environmental damage. Knowledge of the corrosion growth rate is fundamental to pipeline integrity management, as it is essential for risk assessment and decisions related to asset management. This article aimed to compare two approaches for the corrosion growth estimation of the 24-inch offshore gas pipeline: the conventional method versus the Statistically Active Corrosion (SAC) method. This article is based on the in-line inspection (ILI) results of two consecutive assessments from 2020 to 2023 of the entire 73 km of the pipeline. The results show that the SAC method evaluates the corrosion activity on the pipeline with better accuracy and localization than the conventional method, highlighting 782 corrosion active joints in the 5,987 pipeline joints. The SAC method leads to much higher average and maximum corrosion growth rates while also being able to pinpoint active corrosion locations more accurately. Thus, the SAC method is an efficient and simple strategy to cope with corrosion assessment problems regarding pipeline integrity management. It enables the operators to prioritize their maintenance actions, improving pipeline safety.
Doxycycline Suppresses Hypertension through Renin– Angiotensin System (RAS) Regulation: Insights from Molecular Docking and Renal Gene Expression Fajarido, Ariski; Fadilah, Fadilah; Arozal, Wawaimuli; Fatriansyah, Jaka Fajar; Pradana, Agrin Febrian; Monayo, Edwina Rugayah
Molecular and Cellular Biomedical Sciences Vol 10, No 1 (2026)
Publisher : Molecular and Cellular Biomedical Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21705/mcbs.v10i1.744

Abstract

Background: Doxycycline, a tetracycline antibiotic known for inhibiting matrix metalloproteinases, has shown potential antihypertensive effects. However, its role in modulating the renin–angiotensin system remains poorly understood. This study aims to specifically evaluate Doxycycline’s effects on key RAS components and blood pressure responses to clarify its underlying mechanism and support its development as a targeted antihypertensive therapeutic candidate.Materials and Methods: This study integrated an in-silico and experimental approach to assess the antihypertensive effects of doxycycline. Bioinformatics analyses were first conducted, including target prediction, gene ontology enrichment, hub-gene identification, PPI network construction, and KEGG pathway analysis, followed by molecular docking and molecular dynamics simulations to predict doxycycline’s interactions with key RAS targets. To validate these computational findings, qRT-PCR was performed to measure the expression of selected genes in kidney tissues from hypertensive rats.Results: Bioinformatics analysis identified six key target genes, including AGT, AGTR1, AGTR2, REN, ACE, and ACE2. Molecular docking showed that doxycycline exhibited stronger binding affinity to AGTR1 (-8.346 kcal/mol) than its native ligand. Molecular dynamics confirmed the stability of the doxycycline–AGTR1 complex at 20 ns. Gene expression analysis of kidney tissues from hypertensive rats revealed a significant reduction in AGTR1 expression in the group treated with doxycycline 15 mg/kg (p<0.05), while no significant change was observed at 30 mg/kg.Conclusion: Low-dose doxycycline may modulate the renin–angiotensin pathway through AGTR1 inhibition, indicating its potential as a candidate for further antihypertensive research and warranting more comprehensive in vivo evaluation.Keywords: Hypertension, doxycycline, molecular docking, gene expression, Renin-Angiotensin System
Identification Safety Critical Elements and Establish Performance Standards to Control Major Accident Hazard at The Geothermal Power Plant PT. XYZ Febriardy, Febriardy; Fatriansyah, Jaka Fajar; Endang, Endang; Bagaskoro, Farhan Iqbal; Kurniawan, Ari
Journal of Materials Exploration and Findings Vol. 4, No. 3
Publisher : UI Scholars Hub

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Abstract

Geothermal Power Plant (GPP) use steam from geothermal reservoirs to produce electricity. Power Plants are one of the most dangerous work environments. The dangers that exist in the power generation process can be in the form of Major Accident Hazard (MAH) and have a large impact which can cause Major Accidents. Major Accident prevention can be done by managing Safety Critical Elements (SCE) as a control measure in the form of procedures to prevent or mitigate the risks. Each SCE has a Performance Standard that includes targets and thresholds set to reduce risk to reach ALARP (As Low as Reasonably Practicable) that will be used as a reference in Inspection, Testing and Preventive Maintenance programs to prevent Major Accidents. This research was conducted to identify SCE and establish Performance Standard for GPP PT XYZ with a capacity of 1x55 MW. Based on the identification results, it is known that the total MAH at GPP PT XYZ is 112. Each MAH was analyzed using a bow-tie diagram to obtain a total of 532 SCE or 8.12% of the total 6,549 existing equipment.
Surfactant-Controlled Synthesis of Mesoporous Silica from Oil Palm Empty Fruit Bunch Tri Partuti; Donanta Dhaneswara; Jaka Fajar Fatriansyah; Muflikhah Muflikhah; Maria Christina Prihatiningsih
EduChemia: Jurnal Kimia dan Pendidikan Vol 11, No 1 (2026)
Publisher : Department of Chemistr Education Faculty of Teacher Training and Education Universitas Su

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62870/educhemia.v11i1.39110

Abstract

Indonesia is the country that produces the most palm oil worldwide, generating large amounts of oil palm empty fruit bunch (EFB) waste containing silica. The use of EFB waste as a silica precursor offers a sustainable alternative to conventional synthetic sources. Therefore, this study aims to synthesize mesoporous silica from EFB ash via a sol-gel method, using single and mixed surfactant systems, namely, cetyltrimethylammonium bromide (CTAB), Pluronic P123 (P123), and a mixture of CTAB-P123, with a constant mass of 5 grams. The properties of mesoporous silica derived from EFB were characterized using X-ray fluorescence (XRF), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy equipped with energy-dispersive X-ray analysis (SEM-EDX), transmission electron microscopy (TEM), small-angle X-ray scattering (SAXS), and nitrogen adsorption‒desorption measurements based on the BET and BJH methods. The results of this study revealed that the use of Pluronic P123 resulted in a specific surface area of 317.085 m²/g, CTAB (519.951 m²/g), and a mixed-surfactant system (496.547 m2/g). The SAXS results revealed that a mixed CTAB-P123 system produced an ordered mesostructure with a distinct peak at q = 0.1005 Å-1, while a single surfactant formed disordered mesopores. These results demonstrate that the type of surfactant performs an essential function in tailoring the mesoporous characteristics of EFB-derived silica.
Co-Authors Arbi Irsyad Fikri ARI KURNIAWAN Asral, D. Rizal Bagaskoro, Farhan Iqbal Candraningrum, Veronica Hesti Dedi Supriadi Dhaneswara, Donanta Digita, Farhan Rama Eddy S Siradj Elvi Kustiyah Endang Endang, Endang Erlina, Linda Fadilah Fadilah, Fadilah Fadillah Fadillah Fadillah Fadillah Fajarido, Ariski Fauzi, Andrian Febriardy, Febriardy Federico, Andreas Hanifa, Muthia Hanindito Haidar Satrio Hartoyo, Fernanda Jana Hafiza Linda Erlina Linuwih, Baiq Diffa Pakarti Maria Christina Prihatiningsih Mas'ud, Imam Abdillah Mochamad Chalid Monayo, Edwina R Muflikhah Muflikhah Muhammad Anis, Muhammad Muhammad Joshua Yuriansyah Barmaki Nafisah, Helya Chafshoh Nurullia, Zahra Nadia Ovelia, Hanna Paramita, Rafika Indah Pradana, Agrin Febrian Rafika Indah Paramita Ridzuan, Abdul Rahim Rudi Rinaldi, Rudi Salma Ilmiati Surip, Siti Norasmah Surya Dwira Tihara, Irma Hartia Trahmawan, Sigit Tri Partuti Wan Jaafar, Wan Nor Raihan Wawaimuli Arozal Windy Dwininda