cover
Contact Name
Michaud, Patricius F
Contact Email
jurnalmecomare@gmail.com
Phone
+6281360000891
Journal Mail Official
trigin@pelnus.ac.id
Editorial Address
Jl. Cikutra Baru, Bandung, Provinsi Jawa Barat
Location
Kab. bandung,
Jawa barat
INDONESIA
INTERNATIONAL JOURNAL OF MECHANICAL COMPUTATIONAL AND MANUFACTURING RESEARCH
Published by Trigin Publisher
ISSN : 23014148     EISSN : 29623391     DOI : 10.35335/MECOMARE
Core Subject : Engineering,
International Journal of Mechanical Computational And Manufacturing Research invites you to consider submitting original research papers for possible publication after peer review. The scope of this international, scholarly journal is aimed at rapid dissemination of new ideas and techniques and to provide a common forum for significant research and new developments in areas of Mechanical Computational And Manufacturing Research.
Articles 5 Documents
Search results for , issue "Vol. 12 No. 2 (2023): August : Mechanical Computational And Manufacturing Research" : 5 Documents clear
Integration of AHP method in best employee selection: a multi-criteria decision analysis approach for decision making Agung Nugroho; Bambang Winardi; Ajub Ajulian ZM
International Journal of Mechanical Computational and Manufacturing Research Vol. 12 No. 2 (2023): August : Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/computational.v12i2.119

Abstract

In an era of increasingly complex business competition, selecting the best employees has become crucial to ensure organizational productivity and success. In this endeavor, the integration of Multi-Criteria Decision Analysis Method with emphasis on Analytical Hierarchy Process (AHP) has emerged as an objective and scientific approach. This research discusses how the AHP method can be applied in the context of best employee selection by analyzing relevant criteria and pairwise comparisons that are calculated to generate relative weights. Through this process, best employee selection decisions can be made on a stronger and more transparent basis. However, the success of this method depends on the quality of the data and the assumptions used in the calculations. Although complex, AHP can provide valuable insights for decision makers in finding a balance between diverse criteria in the process of selecting the best employee.
Optimization of Inventory Ordering Decision in Retail Business using Exponential Smoothing Approach and Decision Support System Jonhariono Sihotang
International Journal of Mechanical Computational and Manufacturing Research Vol. 12 No. 2 (2023): August : Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/computational.v12i2.121

Abstract

In the context of a challenging retail business, optimizing inventory ordering decisions is crucial to maintain product availability and avoid excessive storage costs. Decision Support System (DSS) approach with the application of exponential smoothing method has emerged as an effective solution to integrate data analysis and more precise decision making. This abstract discusses how exponential smoothing is used in optimizing inventory ordering decisions in retail businesses. We explain the concept of exponential smoothing as a forecasting technique that integrates historical data and future predictions. We also analyze the steps of implementing exponential smoothing in DSS, including smoothing parameters, initialization of initial levels, and forecast calculation. The benefits and challenges in the use of exponential smoothing are discussed in the context of inventory optimization and ordering decision making. The results show that exponential smoothing can provide forecasts that are more adaptive and responsive to changes in demand, with the potential to improve operational efficiency and customer satisfaction. Nonetheless, an understanding of the product characteristics and limitations of the method needs to be considered. This research illustrates how the use of exponential smoothing in DSS can provide valuable guidance for retailers in optimizing inventory and making inventory decisions.
Zk-SNARKs As A Cryptographic Solution For Data Privacy And Security In The Digital Era Imam Santoso; Yuli Christyono
International Journal of Mechanical Computational and Manufacturing Research Vol. 12 No. 2 (2023): August : Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/computational.v12i2.122

Abstract

This research brings the concept of zk-SNARKs (Zero-Knowledge Succinct Non-Interactive Argument of Knowledge) in the context of data security and privacy in the digital world. zk-SNARKs is a cryptographic technology that allows individuals to prove a statement or knowledge without having to reveal the actual details of the information. We illustrate this concept through a simple example of proving age over 18 without revealing the actual date of birth. This research highlights the importance of maintaining data privacy in various technological applications, including the use of zk-SNARKs in blockchain to maintain transaction privacy and personal data protection in increasingly sophisticated applications. However, the implementation of zk-SNARKs requires deep mathematical understanding and strong data security concerns. With great potential to support data privacy and security in the evolving digital era, zk-SNARKs is a highly relevant tool in addressing privacy-related challenges in the digital world. The conclusion of this research is that zk-SNARKs is an important tool in maintaining data privacy and security in the digital age. With its ability to allow individuals to prove knowledge or assertions without revealing actual details of information, this technology has wide applications in various sectors, including finance, data management, and data privacy protection. However, it should be emphasized that the implementation of zk-SNARKs requires extra care in securing the system and ensuring that the technology is used properly to maintain high data privacy and security. With further development and understanding in this technology, zk-SNARKs can be an integral component in building a safer and more private digital world.
Comparasion of composition of brake pad hardness and wearness Mulia Mulia
International Journal of Mechanical Computational and Manufacturing Research Vol. 12 No. 2 (2023): August : Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/computational.v12i2.123

Abstract

This study aims to identify the most optimal material composition in achieving the best combination of hardness and wear. The experimental method was conducted using a special test bed designed to test the mechanical properties of various material compositions. The material specimens used were weighed before and after the test to calculate the wear rate by observing the change in specimen mass. The results showed that the 50:50 material composition performed significantly better than the 60:40 composition in terms of hardness and wear properties. These findings suggest that the 50:50 composition may be a superior choice in various applications where a combination of strength and wear resistance is required, such as in the manufacturing industry, materials engineering, or the automotive sector. This research provides valuable insights into material selection that can improve the performance and durability of the final product.
Analysis of the effect of operational load fluctuations on heavy vehicle gearbox wear Mulia Mulia; Supriadi Supriadi; Suardi Suardi
International Journal of Mechanical Computational and Manufacturing Research Vol. 12 No. 2 (2023): August : Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/computational.v12i2.124

Abstract

This research focuses on the wear analysis of heavy vehicle gearbox systems, with particular emphasis on the case study of operational load fluctuations as a factor influencing wear rates. Heavy vehicles play a central role in various industries, and gearboxes are key components that affect operational performance and reliability. In this study, we collected operational data from various heavy vehicles operating under various conditions and environments. Through rigorous statistical analysis, we were able to identify a significant relationship between operational load fluctuations and gearbox wear rates. The results indicate that an increase in operational load fluctuations can proportionally increase the wear rate. These results have important implications in the development of smarter and more efficient maintenance strategies for heavy vehicles, which can reduce unexpected maintenance costs and increase gearbox service life. In addition, this study also confirmed that the basic assumptions in regression analysis, such as normality of residuals, homoscedasticity, and independence of residuals, were well met. This validates the results of the regression analysis and provides a solid basis for decision-making in the context of heavy vehicle maintenance. Recommendations for further research development include more detailed data collection, the use of more advanced analysis methods, and the application of sensor and IoT technologies for real-time monitoring. With continued research in this area, we can advance our understanding of wear on heavy vehicle gearboxes and support the development of smarter maintenance strategies in the heavy transportation industry.

Page 1 of 1 | Total Record : 5


Filter by Year

2023 2023


Filter By Issues
All Issue Vol. 14 No. 3 (2025): Nov-Feb 2026: INPRESS Vol. 14 No. 2 (2025): August: Mechanical Computational And Manufacturing Research Vol. 14 No. 1 (2025): May: Mechanical Computational And Manufacturing Research Vol. 13 No. 4 (2025): February: Mechanical Computational And Manufacturing Research Vol. 13 No. 3 (2024): November: Mechanical Computational And Manufacturing Research Vol. 13 No. 2 (2024): August: Mechanical Computational And Manufacturing Research Vol. 13 No. 1 (2024): May: Mechanical Computational And Manufacturing Research Vol. 12 No. 4 (2024): February : Mechanical Computational And Manufacturing Research Vol. 12 No. 3 (2023): November: Mechanical Computational And Manufacturing Research Vol. 12 No. 2 (2023): August : Mechanical Computational And Manufacturing Research Vol. 12 No. 1 (2023): May: Mechanical Computational And Manufacturing Research Vol. 11 No. 4 (2023): February: Mechanical Computational And Manufacturing Research Vol. 11 No. 3 (2022): November: Mechanical Computational And Manufacturing Research Vol. 11 No. 2 (2022): August: Mechanical Computational And Manufacturing Research Vol. 11 No. 1 (2022): May: Mechanical Computational And Manufacturing Research Vol. 10 No. 4 (2022): February: Mechanical Computational And Manufacturing Research Vol. 10 No. 3 (2021): November: Mechanical Computational And Manufacturing Research Vol. 10 No. 2 (2021): August: Mechanical Computational And Manufacturing Research Vol. 10 No. 1 (2021): May: Mechanical Computational And Manufacturing Research Vol. 9 No. 4 (2021): February: Mechanical Computational And Manufacturing Research Vol. 9 No. 3 (2020): November: Mechanical Computational And Manufacturing Research More Issue