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All Journal Syntax Literate: Jurnal Ilmiah Indonesia Indonesian Journal of Chemistry Eksakta : Berkala Ilmiah Bidang MIPA Abdi Dosen : Jurnal Pengabdian Pada Masyarakat Journal of Materials Exploration and Findings (JMEF)
Fatriansyah, Jaka Fajar
Department Of Metallurgical And Materials Engineering, Faculty Of Engineering, Universitas Indonesia, Kampus Depok, West Java 16424, Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Energy Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences Other

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Synthesis and Characterization of Lignin-Based Polyurethane as a Potential Compatibilizer Salma Ilmiati; Jana Hafiza; Jaka Fajar Fatriansyah; Elvi Kustiyah; Mochamad Chalid
Indonesian Journal of Chemistry Vol 18, No 3 (2018)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (672.597 KB) | DOI: 10.22146/ijc.27176

Abstract

Lignin is one of the most abundant biopolymer on earth. It has polar and non-polar side due to its hyperbranched structure, but the polarity of lignin has a higher tendency than non-polarity. Lignin has potential to be compatibilizer if the portion of non-polar can be increased. This research is focused on investigate the synthesis of lignin-based polyurethane to enhance the portion of non-polarity in lignin. Lignin-based polyurethane was prepared by reacting variation 4,4'-Methylenebis(cyclohexyl isocyanate) (HMDI) and polyethylene glycol (PEG), then lignin was added to the reaction. In this study, the structure of lignin-based polyurethane was confirmed by NMR and FTIR. NMR and FTIR showed that lignin successfully grafted. NMR, also used to investigate the variation molar mass of PEG and isocyanate contents effects to polarity of lignin-based polyurethane. The polarity of lignin-based polyurethane decrease as the composition of HMDI and molecular weight of PEG increase. This result also occurs on the sessile drop test that used to determine surface tension of lignin-based polyurethane. The thermal properties of lignin-based polyurethane also investigate using STA. Based on STA, enhancement of composition of HMDI and PEG increase thermal degradation and resistance of lignin-based polyurethane.
Simulation of Melt Viscosity Effect on the Rate of Solidification in Polymer Jaka Fajar Fatriansyah; Hanindito Haidar Satrio; Muhammad Joshua Yuriansyah Barmaki; Arbi Irsyad Fikri; Mochamad Chalid
Indonesian Journal of Chemistry Vol 19, No 2 (2019)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (227.644 KB) | DOI: 10.22146/ijc.27195

Abstract

Phase field model has been successfully derived from ordinary metal phase field equation to simulate the behavior of semi-crystalline polymer solidification phenomenon. To obtain the polymer phase field model, a non-conserved phase field equation can be expanded to include the unique polymer parameters, which do not exist in metals, for example, polymer melt viscosity and diffusion coefficient. In order to expand this model, we include free energy density and non-local free energy density based on Harrowel-Oxtoby and Ginzburg-Landau theorem for polymers. The expansion principle for a higher order of binary phase field parameter was employed to obtain fully modified phase field equation. To optimize the final properties of the products, the solidification phenomenon in polymers is very important. Here, we use our modified equation to investigate the effect of melt viscosity on the rate of solidification by employing ordinary differential equation numerical methods. It was found that the rate of solidification is related to the melting temperature and the kinetic coefficient.
Preface of Volume 1 Issue 1 on Journal of Materials Exploration and Findings (JMEF) Fatriansyah, Jaka Fajar
Journal of Materials Exploration and Findings Vol. 1, No. 1
Publisher : UI Scholars Hub

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Abstract

The Optimization Of Failure Risk Estimation On The Uniform Corrosion Rate With A Non-Linear Function Hartoyo, Fernanda; Fatriansyah, Jaka Fajar; Mas'ud, Imam Abdillah; Digita, Farhan Rama; Ovelia, Hanna; Asral, Datu Rizal
Journal of Materials Exploration and Findings Vol. 1, No. 1
Publisher : UI Scholars Hub

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Abstract

Failures in the oil and gas pipeline system are conditions that must be avoided and anticipated because the losses due to the failures can occur at a very high level. Internal corrosion is one of the significant causes of the failures in pipeline systems. In addition, this type of corrosion is due to the high content of carbon dioxide and other corrosive substances in crude oil and natural gas. Therefore, an optimal inspection scheduling system is required to prevent the possibility of pipeline failures due to corrosion and to avoid any overspending on the budget due to excessive inspection scheduling. Risk-based testing (RBI) is one of the best methods to define a test planning system by using an optimal risk assessment. In this article, a Monte Carlo random number generator is applied by using a huge number of random iterations to approximate the actual risk value of a pipeline system with a limited sample at the scene. The nonlinear corrosion rate function is used for comparison with the commonly used linear corrosion rate function based on ASTM G-16 95. Once a risk value is estimated, the value is monitored based on an assessment of the risk matrix for each corrosion rate function by using the RBI method. The results show that the nonlinear corrosion rate function provides a more accurate approach to estimating the actual risk value and ultimately leads to an optimal inspection planning system.
Investigating Features and Output Correlation Coefficient of Natural Fiber-Reinforced Poly(lactic acid) Biocomposites Federico, Andreas; Surip, Siti Norasmah; Wan Jaafar, Wan Nor Raihan; Fatriansyah, Jaka Fajar; Pradana, Agrin Febrian
Journal of Materials Exploration and Findings Vol. 1, No. 1
Publisher : UI Scholars Hub

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Abstract

Polylactic acid (PLA) material has the potential to be applied in various industrial fields, but this material has shortcomings in terms of mechanical properties, especially mechanical strength, due to brittleness nature of PLA. The manufacture of PLA composite material with the addition of natural fibers as a reinforcing phase is one of the methods to increase the impact strength and maintain the biodegradable properties of the material. However, in theory, there are many factors that affect the mechanical properties of composite materials, thus making the mechanical properties of composites more complex than monolithic materials. The mechanical properties of these composite materials can be predicted using deep learning by paying attention to the relationship between factors, and between factors and their mechanical properties. This relationship has an important role in creating a predictive model with good accuracy. Therefore, correlation analysis is an important thing to do. Correlation analysis was applied using Python programming language to determine the relationship between the impact strength of natural fiber-reinforced PLA biocomposites with its feature information: chemical composition, density, dimensions, surface chemical treatment of natural fibers, matrix-reinforcement volume fraction, and the type of processing used to manufacture the material.
STUDY OF CORRELATION OF CHICKEN EGGS PRODUCTION TO CALORIE CONSUMPTION AND PREVALENCE OF POOR NUTRITION TO CHILDREN (0-59 MONTHS): COMMUNITY SERVICE SURVEY Jaka Fajar Fatriansyah; Agrin Febrian Pradana; Ignatius Egan Jonatan; Andreas Federico; Muhammad Joshua Yuriansyah Barmaki; Andrian Fauzi; Muhammad Syaikh Rohman
Abdi Dosen : Jurnal Pengabdian Pada Masyarakat Vol. 6 No. 4 (2022): DESEMBER
Publisher : LPPM Univ. Ibn Khaldun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32832/abdidos.v6i4.1421

Abstract

Indonesia is a country with low consumption of chicken eggs and this has implications for the high prevalence of malnutrition among children under five in Indonesia. In this community service survey research, an analysis of the correlation between chicken egg production and calorie consumption will be carried out as the prevalence of under-five malnutrition (0-59 months). The analysis carried out is Pearson correlation analysis. The study found that there was a positive correlation between egg production per capita and egg consumption per province with a correlation coefficient of 2.067 x 103 tons/kcal. In addition, there is also a negative correlation between egg consumption and the prevalence of malnutrition in children under five (0-59 months). This study obtained a recommendation that it is important to increase egg production by increasing the productivity of chicken egg SMEs in the community service scheme.
Ligand Based Pharmacophore Modelling, Virtual Screening, Molecular Docking, and ADMETOX of Natural Compounds as Antibiotic Candidates against Urinary Tract Infections (UTI) Windy Dwininda; Linda Erlina; Rafika Indah Paramita; Fadillah Fadillah; Surya Dwira; Jaka Fajar Fatriansyah
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 24 No. 02 (2023): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol24-iss02/404

Abstract

The use of antibiotic drugs requires close supervision that patients take antibiotics according to the rules. Irregular antibiotic use led to increased ADR cases (Antibiotic Drug-resistant). ADR is when an individual becomes resistant to an antibiotic drug that cannot kill bacteria. The high number of ADR cases prompted drug discovery to be implemented in analysis for Antibiotic candidates with good effectiveness through the Molecular Docking approach. The search for candidate test compounds as antibiotics were performed using the pharmacophore modelling method and molecular docking. And piperine, withaferin, has some of the same amino acids Ala101, Val103, Glu166, Trp165, and Leu102. Based on the prediction of the promising potential test ligand compound is Corosolic acid. In addition to assessing drug-likeness, pharmacokinetic and toxicity parameters, corosolic acid also has the lowest binding energy among other compounds. Through a textual bioinformatics approach, molecular docking simulations can be used as a first step in the search for new drug candidates in silico by considering various aspects, starting from the physicochemical properties of protein-ligand compounds and the environment. Analysis during the docking process to ADMETOX is an analysis to see the effectiveness and in silico compound safety.  
Perancangan Program Pengestimasi Probabilitas Kegagalan Peralatan Penukar Panas Akibat Korosi Seragam Berbasis Deep Neural Network Jaka Fajar Fatriansyah; Donanta Dhaneswara; Muthia Hanifa; Fernanda Hartoyo; Agrin Febrian Pradana; Muhammad Anis; Andrian Fauzi
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.
Pipeline Risk Analysis Optimization with Monte Carlo Method Using Gamma Distribution Digita, Farhan Rama; Fatriansyah, Jaka Fajar; Ridzuan, Abdul Rahim; Ovelia, Hanna; Mas'ud, Imam Abdillah; Tihara, Irma Hartia; Linuwih, Baiq Diffa Pakarti
Journal of Materials Exploration and Findings Vol. 2, No. 3
Publisher : UI Scholars Hub

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Abstract

The inspection process of piping components in the oil and gas industry is one of the most crucial things, given the high risk posed by pipeline system failures, which have a huge impact on losses, both from environmental and financial aspects. Risk-based inspection with the Monte Carlo method is one of the efforts that can be made to minimize failures in piping systems, by involving data distribution to calculate the probability of component failure. Although the normal distribution is commonly used for generating random variables, its use in corrosion rate calculation can lead to overestimation due to negative corrosion rate values. Overestimation can result in inaccurate data and higher risk values, which can cause increased inspection costs. Therefore, the use of gamma distribution as a random variable generator can be a solution to reduce the bias level and increase the accuracy of the normal distribution analysis results. The gamma distribution is proven to prevent overestimation, so it can avoid inspection cost losses because the resulting risk value is lower than the normal distribution.
Development of Dynamic Risk-Based Inspection Using Forward Difference Approach for Pipe Failure Due to Uniform Corrosion Fatriansyah, Jaka Fajar; Nurullia, Zahra Nadia; Federico, Andreas; Priadi, Dedi
Journal of Materials Exploration and Findings Vol. 2, No. 1
Publisher : UI Scholars Hub

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Abstract

The oil and gas industry is one of the world's largest and most influential energy contributors. All aspects involved in the operation of this industry are fundamental to be reviewed and managed correctly, especially by preventing or minimizing the failures that could occur. Uniform corrosion is the most common component failure mechanism that can cause failure in the oil and gas industry. The company's actions in managing and preventing the risk of this type of failure have a major role in the sustainability of the company due to the possibility of more significant impacts if the risk cannot be handled well, such as high inspection and handling costs, environmental impacts, and threats to work safety. In this study, the Dynamic Risk-Based Inspection (DRBI) method, which is a development of Risk-Based Inspection (RBI), is implemented to handle and analyze risks that are managed in real-time at each inspection period. Risk level analysis was carried out through data processing related to pipe thickness from the risk profile from the inspection results in 5 months using Igor and Rstudio software and calculating corrosion rates using the forward difference approach. Based on the analysis results, five risk levels of pipeline failure at PT. X due to uniform corrosion using DRBI was obtained, consisting of two medium risks and three medium-high risks. In contrast, only one risk level was obtained from the RBI method, namely medium-high. The risk value fluctuates greatly every month, causing the DRBI method to have a higher level of accuracy and the ability to detect potential risks in more detail than the RBI method.
Co-Authors Agrin Febrian Pradana Agrin Febrian Pradana Andreas Federico Andrian Fauzi Andrian Fauzi Arbi Irsyad Fikri Asral, Datu Rizal Candraningrum, Veronica Hesti Dedi Supriadi Dhaneswara, Donanta Digita, Farhan Rama Dwira, Surya Elvi Kustiyah Erlina, Linda Fadillah Fadillah Fadillah Fadillah Federico, Andreas Fernanda Hartoyo Hanindito Haidar Satrio Hartoyo, Fernanda Ignatius Egan Jonatan Jana Hafiza Linda Erlina Linuwih, Baiq Diffa Pakarti Mas'ud, Imam Abdillah Mochamad Chalid Muhammad Anis Muhammad Joshua Yuriansyah Barmaki Muhammad Joshua Yuriansyah Barmaki Muhammad Syaikh Rohman Muthia Hanifa Nafisah, Helya Chafshoh Nurullia, Zahra Nadia Ovelia, Hanna Paramita, Rafika Indah Pradana, Agrin Febrian Rafika Indah Paramita Ridzuan, Abdul Rahim Salma Ilmiati Surip, Siti Norasmah Surya Dwira Tihara, Irma Hartia Wan Jaafar, Wan Nor Raihan Windy Dwininda