Article Per Year (5 Year)
p-Index From 2021 - 2026
1.819
P-Index
This Author published in this journals
All Journal Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Rekayasa Mesin Journal of Energy, Mechanical, Material and Manufacturing Engineering Jurnal Teknik Mesin Indonesia Mechanical Engineering for Society and Industry Prosiding Simposium Nasional Rekayasa Aplikasi Perancangan dan Industri National Multidisciplinary Sciences
Mujianto, Agus
Unknown Affiliation
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences Transportation

Published : 12 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 12 Documents
Search

 1   2 
OPTIMIZATION OF TENSILE STRENGTH OF EMPTY OIL PALM FRUIT BUNCH FIBER REINFORCED COMPOSITES USING GENETIC ALGORITHMS Rahim, Abdul; Mujianto, Agus; Feriyanto, Richie; Waloyo, Hery Tri
Jurnal Rekayasa Mesin Vol. 15 No. 3 (2024)
Publisher : Jurusan Teknik Mesin, Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jrm.v15i3.1898

Abstract

The use of natural materials such as oil palm empty fruit bunch fibers can provide a solution to increase value-added and manage plantation waste. Fibers are combined with a matrix to create composite materials. Instead of glass fibers, environmentally friendly natural fibers serve as the reinforcement in the composite material. Implementing natural fiber composites must consider the primary construction requirement, which is tensile strength. Artificial intelligence like genetic algorithms (GA) can simplify and reduce costs in the search for optimal values in composite material engineering. Data is obtained through experimental testing prepared samples and subsequently used as input for GA. The input parameters consist of three variables such as soaking time, volume fraction, and fiber length. The output of the optimization process is tensile strength. The maximum tensile strength has already been achieved with genetic crossover by the 125th generation. Based on GA calculations, the optimal parameters obtained are soaking time of 6.2 hours, volume fraction of 29.6%, and fiber length of 6.9 cm. The predicted optimal tensile strength value is 4.78 MPa.
SOFT MAGNETIC COMPOSITE (SMC) ANALISIS DENGAN BIBLIOMETRIC Waloyo, Hery Tri; Kurniawan, Krisna Budi; Ahmad, Fauzi; Putra, Ferdiansyah; Fauzan, M. Afif; Firmansyah, Muhammad Gilang; Mujianto, Agus
Jurnal Rekayasa Mesin Vol. 16 No. 1 (2025)
Publisher : Jurusan Teknik Mesin, Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jrm.v16i1.1917

Abstract

Soft Magnetic Composite (SMC) is a composite material made by binding iron (Fe) powder with non-magnetic materials such as epoxy resin. The main properties of SMC, which have high electrical resistance yet can efficiently conduct magnetic fields, make it a primary choice for various applications that require efficiency, reliability, and high performance. Extensive research has been conducted on SMC, making it necessary to perform a bibliometric analysis to categorize and observe developments in SMC research. The main objectives of this study are to understand patterns in scientific publications, identify the most productive research developments, determine research linkages, and identify collaboration networks related to SMC. A total of 1067 documents, 347 sources, and 2113 authors were recorded in the Scopus database between 2005 and 2024. The number of article publications has increased annually by 4.36%. China is the most productive country and also has the most extensive international collaboration networks. The majority of publications are published in journals with specific topics, primarily focusing on magnetics and magnetic materials.
Co-Authors A.N. Afandi Abdul Gani Abdul Rahim Abdul Rahim Adriyanto, Feri Ahmad, Fauzi Ananta, Eka Mahdi Andi Nugroho, Andi Anis Siti Nurrohkayati Fauzan, M. Afif Febriansyah, Kholiq Ferdiansyah Putra Feriyanto, Richie Firmansyah, Muhammad Gilang Gunadin, Indar Chaerah Hery Tri Waloyo Karya Saputra, Didy Khanif Setiyawan Kurniawan, Krisna Budi Muhammad Nizam Nur Prapanca, Agusti Putra, Mufti Reza Aulia Santoso, Henry Probo Setiawan, Khanif Sudirman Sudirman Waluyo, Hery Try