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All Journal Syntax Literate: Jurnal Ilmiah Indonesia Jurnal Pendidikan Kimia (JPKim) Journal of Materials Exploration and Findings Jurna Beta Kimia
Pradana, Agrin Febrian
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Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Education Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences Other

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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

Show Abstract | Download Original | Original Source | Check in Google Scholar

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.
The potential of methanol extract nanoemulsion from gletang flower (Tridax procumbens) as an antibacterial agent against pathogenic bacteria Sriwijayanti, Sriwijayanti; Pradana, Agrin Febrian; Fauji, Fajar Rizki; Farlina, Iin; Situmeang, Boima
Jurnal Pendidikan Kimia Vol. 16 No. 3 (2024): J. Pendidik. Kim : December 2024
Publisher : Pascasarjana Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/jpkim.v16i3.65168

Abstract

Gletang plant is a weed that grows wild and is widely distributed in various places such as rice fields, plantations, and roadsides. Phytochemical screening of gletang flower extract using methanol revealed the presence of secondary metabolites such as alkaloids, flavonoids, steroids, phenols, terpenoids, and tannins. This study aims to formulate a nanoemulsion from the methanol extract of gletang flowers. The extraction was performed by maceration with methanol 96%. The nanoemulsion was characterized by testing its pH, % transmittance, stability, viscosity and particle size using a particle size analyzer. The antibacterial activity was tested against Staphylococcus aureus and Escherichia coliusing the Kirby-Bauer method. The results of pH characterization, % transmittance, stability and viscosity tests met the standards. The particle size analyzer showed that the particle size ranged between 300-1000 nm. The antibacterial activity tests indicated that all three formulations showed activity against the pathogenic bacteria E. coli, with formulation 3 showing the highest activity.
Microemulsion of methanol extract of Tridax procumbens flower and its antibacterial activity against Streptococcus mutans and Enterococcus faecalis Wijayanti, Sri; Pradana, Agrin Febrian; Situmeang, Boima; Prastiwi, Dina Alva; Musa, Weny J.A.
Jurnal Beta Kimia Vol 5 No 1 (2025): Volume 5 Number 1, May 2025
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jbk.v5i1.21189

Abstract

Tridax procumbens (commonly known as Gletang flower) is a medicinal plant recognized for its antibacterial potential and is widely distributed across various habitats such as rice fields, plantations, and roadsides. Phytochemical screening of its methanolic flower extract revealed the presence of secondary metabolites, including alkaloids, flavonoids, steroids, phenols, terpenoids, and tannins, all of which contribute to its biological activities. This study aimed to develop a microemulsion formulation of T. procumbens methanolic extract and to evaluate its antibacterial activity against Streptococcus mutans and Enterococcus faecalis, two major oral pathogenic bacteria. The microemulsion was prepared using the sonication method and characterized by assessing its pH, transmittance, viscosity, physical stability, and particle size using a particle size analyzer. Antibacterial activity was tested using the Kirby-Bauer disk diffusion method. The results indicated that the microemulsion had particle sizes ranging from 300–1000 nm and demonstrated significantly higher antibacterial activity compared to the crude extract, suggesting improved solubility and enhanced bioactivity of the active compounds. This formulation holds promise as a natural antibacterial agent for the prevention of oral infections.
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.
Co-Authors Dhaneswara, Donanta Fatriansyah, Jaka Fajar Fauji, Fajar Rizki Fauzi, Andrian Federico, Andreas Hanifa, Muthia Hartoyo, Fernanda iin Farlina, iin Muhammad Anis, Muhammad Musa, Weny J.A. Prastiwi, Dina Alva Situmeang, Boima Sri Wijayanti Sriwijayanti, Sriwijayanti Surip, Siti Norasmah Wan Jaafar, Wan Nor Raihan