cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
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,
Automotive Engineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Mechanical 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.
Arjuna Subject : Teknik (semua kategori) - Komputasi Mekanik
Articles 95 Documents
 6   7   8   9   10 
Implementation of the Simple Multi-Attribute Rating Technique for Determining Home Ownership Loan Housing Wahidin, Ahmad Jurnaidi; Nabila Sari, Marhani
International Journal of Mechanical Computational and Manufacturing Research Vol. 13 No. 2 (2024): August: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/computational.v13i2.174

Abstract

This study applied the Simple Multi-Attribute Rating Technique (SMART) to determine the best housing option based on Home Ownership Loans. Five criteria were identified as crucial for Home Ownership Loans housing evaluation: price, location, facilities, land area, and building area. Each criterion was assigned a weight reflecting its relative importance in the decision-making process. Four housing alternatives were evaluated using a rating scale to measure how well each met the criteria. The evaluation showed that Magnolia Residence was the top-ranked housing option with a total score of 0.73, followed by Puri Jaya, Widari Village, and CitraRaya Tangerang. The SMART method proved effective in assisting prospective buyers in making informed and objective decisions when selecting Home Ownership Loans housing. Future research is recommended to include additional criteria, expand housing alternatives, involve more respondents, and develop web-based or mobile applications to facilitate the use of the SMART method
Compressive strength of concrete mixtures of phosphorus powder and glass powder in concrete of grade FC'20 MPA Hartanto, Adrian; Rini, Rini; Nasution, Ridwan
International Journal of Mechanical Computational and Manufacturing Research Vol. 13 No. 1 (2024): May: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

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

Abstract

The research objective in this study is to analyze the effect of substitution of phosphorus powder and glass powder which has an impact on the compressive strength of 20 Mpa fc concrete and to find out the results of testing the compressive strength of concrete with added phosphorus and glass powder at ages 7 days, 14 days, 21 days and 28 days. From the research results, it was found that the compressive strength value of concrete aged 7 days in variations of 3% Glass concrete and 0.35% Phosphorus decreased compared to normal concrete with a ratio of 43%, in variations of Glass concrete 5% and 0.35% Phosphorus decreased compared to normal concrete with a ratio 53% and in the Glass concrete variation 7% & 0.35% Phosphorus decreased to 45.5%. At the age of 14 days in the Glass concrete variation of 3% and 0.35% Phosphorus decreased compared to normal concrete with a ratio of 26%, in the Glass concrete variation of 5% and 0.35% Phosphorus decreased compared to normal concrete with a ratio of 21% and in the Glass concrete variation 7% & 0.35% Phosphorus decreases up to 20%. At 21 days, the Glass concrete variation of 3% and 0.35% Phosphorus increased compared to normal concrete with a ratio of 6.5%, the Glass concrete variation of 5% and 0.35% Phosphorus decreased compared to normal concrete with a ratio of 6% and the Glass concrete variation 7% & 0.35% Phosphorus decreases up to 11%. At 28 days in the Glass concrete variation of 3% and 0.35% Phosphorus increased compared to normal concrete with a ratio of 1.10%, in the Glass concrete variation of 5% and 0.35% Phosphorus decreased compared to normal concrete with a ratio of 0.95% and in the Glass concrete variation 7 % & 0.35% Phosphorus decreased to 18.02%.
Identification of hardness values of boiler pipes after heating and without heating process Mulia, Mulia; Suardi, Suardi; Susilo, Hendra; Sinurat, Fadlah K.; Supriadi, Supriadi
International Journal of Mechanical Computational and Manufacturing Research Vol. 13 No. 2 (2024): August: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

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

Abstract

Boilers operate at high pressure and high temperature. When the life of the boiler pipe reaches its limit, failure will occur. High temperatures on the outside of the pipe, high pressure inside, and also flames that have been contaminated with corrosive residues for a long amount of time will cause pipe failure. The purpose of the study was to identify the hardness value of boiler pipes after experiencing the heating process and without heating on ASTM A179 pipes. The research method carried out is starting from the preparation of tools and materials, cutting small materials (making specimens), hardness testing, data processing, data analysis and drawing conclusions. The research results are as follows: 1) Obtained average hardness values on standard ASTM A179 pipes in boilers with each brinell, Rockwell, and Vickerss test of 63.67 HRB, 45.20 HRC, and 85.20 HV. 2). The average hardness value of ASTM A179 pipes affected by boiler combustion chamber temperature with each brinell, Rockwell, and Vickerss test is 76 HRB, 50.40 HRC, and 202.30 HV. 3) The value of hardness test results on standard ASTM A179 pipes comparing with after heating has increased hardness in each brinell test by 63.67: 76 HRB, Rockwell by 24.20: 50.40 HRC, and Vickerss of 85.20: 202.30 HV.
Electricity demand forecasting in Ambon using machine learning techniques Herjuna, Silvester Adi Surya; Budisusila, Eka Nuryanto; Haddin, Muhammad
International Journal of Mechanical Computational and Manufacturing Research Vol. 13 No. 2 (2024): August: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/computational.v13i2.179

Abstract

This study aims to analyze the impact of electrical load forecasting using Artificial Neural Networks (ANN) to improve power supply reliability and efficiency in Ambon’s electric system. The objective is to develop a reliable forecasting model that supports effective energy management, helping to achieve operational excellence in terms of quality, safety, and cost-efficiency. A quantitative approach was utilized, gathering historical electricity load data from 2019 to 2024, alongside relevant environmental and temporal factors. The data were analyzed using ANN within a Python-based framework to predict future electricity demands accurately. The study employs a structured equation modeling to validate the forecasting model and its components. The findings reveal that the ANN model effectively predicts electrical loads with high accuracy, demonstrating substantial improvements in operational efficiency and energy cost reductions. The model’s ability to incorporate multiple input variables allows for nuanced understanding and prediction of load variations, thereby facilitating better resource allocation and strategic planning. This research contributes uniquely by applying ANN for electrical load forecasting in the context of Ambon’s electrical system, underscoring the integration of AI techniques in improving the operational efficiency of power utilities. The study extends the knowledge on the application of machine learning in the power sector by demonstrating how sophisticated forecasting models can significantly enhance energy management strategies
Influence Speed High-Speed Steel Chisel Cut Against Integrity Carbon Steel Surface Sumantri, Ricky; Nasution, M. Zakaria Alhafiz
International Journal of Mechanical Computational and Manufacturing Research Vol. 13 No. 2 (2024): August: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

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

Abstract

This research aims to investigate the Influence of High-Speed Steel Cutting Tool Speed on the Surface Integrity of Low Carbon Steel. Low carbon steel is a commonly used material in the industry due to its strength and corrosion resistance. However, the steel processing processes diminish its quality and service life. In this study, variations in high-speed steel cutting tool speeds were used to examine their influence on the surface integrity of low carbon steel. The research results indicate that the cutting speed of high-speed steel tools has a significant impact on the surface integrity of low carbon steel. It was found that increasing the cutting speed can reduce surface damage and make the surface smoother, thereby improving the quality and service life of low carbon steel. However, excessively high cutting speeds can also lead to overheating and excessive wear. Additionally, other factors such as cutting fineness and tool conditions need to be considered in maintaining the surface integrity of low carbon steel. This research provides a better understanding of the relationship between high-speed steel cutting tool speed and the surface integrity of low carbon steel, which can be used as a guideline in the low carbon steel processing to optimize quality and efficiency.
Comparison of the Naïve Bayes Method and Support Vector Machine in Sentiment Analysis of Genshin Impact Game Reviews Pratama, Mr. Aldiansyah; Hasan, Fuad Nur
International Journal of Mechanical Computational and Manufacturing Research Vol. 13 No. 2 (2024): August: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/computational.v13i2.198

Abstract

Genshin Impact was a successful and quite popular game during the 4 years of its release, but behind this there are several positive or negative opinions about this game, both internal and external. Sentiment Analysis is a technique that can identify an opinion in a text that is managed, be it a comment or review. The aim of the research is to compare two algorithms, namely Support Vector Machine and Naïve Bayes, in classifying Genshin Impact game reviews on Google Playstore. This method has several stages, namely crawling data, text preprocessing, using a confusion matrix and k-fold cross validation, all of these stages are carried out using libraries in Python with 1198 review data divided between test data and training data by 90:10 which produces a support vector machine of 73% accuracy, 75% precision, 64% recall and f1-score of 64% while naïve bayes is 72% accuracy, 68% precision, 68% recall and f1-score of 68%. With this comparison it is concluded that support vector machine has a higher evaluation value than naïve bayes, while it is known that the majority of review data has a negative value regarding Genshin Impact game reviews.
Value Stream Mapping for Warehouse Process in Automotive Manufacturing Case Maryadi, Deri; Moulita, R.A Nurul; Luther King, Marthin; Maria Veranika, Rita; Madagaskar, Madagaskar
International Journal of Mechanical Computational and Manufacturing Research Vol. 13 No. 3 (2024): November: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/computational.v13i3.199

Abstract

KD parts warehouse is a transit and connection place before the KD parts (Knock Down) car’s body and material from Automotive manufacturing, to export destination in several countries or destination. The faster the warehouse operation process will make the company's export performance better. This research aims to reduce NVA and NNVA activities' concern in warehouse KD operations in Japanese automotive manufacturers in Cikarang. The application of lean thinking with the VSM (Value Stream Mapping) approach eliminates the waste of activities and processes in the KD warehouse. From the CVSM and PMA (Process Mapping Analysis) results, the work efficiency is 63%, with NVA time of 244.5 minutes and an NNVA time of 471 minutes. In the future state map, the work efficiency becomes 82% due to kaizen improvement, re-layout, and process redesign in the warehouse, with the total NVA become zero and NNVA reduce to 177 minutes.
Solar energy demonstrator design and testing series circuit with 350 panel tilt angle in the sunrise and sunset direction Susilo, Hendra; Mulia, Mulia; Sinurat, Fadlah K.; Supriadi, Supriadi; Suardi, Suardi
International Journal of Mechanical Computational and Manufacturing Research Vol. 13 No. 3 (2024): November: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/computational.v13i3.231

Abstract

This research focuses on the design of a solar energy demonstrator with a 35-degree tilted panel configuration, as well as testing its performance in orientation towards sunrise and sunset in real environmental conditions. The evaluation was conducted to analyze the effect of tilt angle and orientation on the efficiency of the solar panel system. The tests were conducted for five days (October 07-12) between 8 a.m. and 4 p.m. The maximum power was achieved at 10 a.m. and 10 p.m., respectively. Maximum power was achieved from 10:00 to 12:00, with a peak of 70 watts on October 07, indicating optimal conditions for sunlight absorption. In contrast, the power generated in the morning (08.00-09.00) and afternoon (15.00-16.00) was lower, ranging from 10-30 watts, due to lower solar intensity. In terms of efficiency, the highest peak reached 50% at 10:00 to 12:00 on October 07, while in the morning and afternoon, the efficiency decreased to 10-20%. The difference between days was influenced by weather conditions, with October 07 and 08 having higher power and efficiency. This research shows the importance of tilt angle, orientation, time of day, and weather conditions in determining the optimal performance of solar panels.
The effectiveness of digital twin in reducing downtime in the manufacturing industry: A literature analysis S, Pipiet Mutiara Tri.; Nurraihan, Faiq
International Journal of Mechanical Computational and Manufacturing Research Vol. 13 No. 4 (2025): February: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/computational.v13i4.206

Abstract

The Digital Twin is an innovative technology that significantly enhances operational efficiency and production in the industrial sector. This research seeks to examine the role of Digital Twin in mitigating both scheduled and unscheduled downtime, along with the technical and non-technical elements that affect its implementation efficacy. Literature review revealed that Digital Twin facilitates real-time monitoring, precise data analysis, and enhanced process modelling, all of which aid in minimising downtime. Moreover, elements such as system integration, data quality, organisational culture, and managerial support are essential for the successful application of this technology. The research findings indicate that appropriate investment in technological infrastructure and the formulation of management strategies that foster innovation enable organisations to optimise the advantages of Digital Twin. Companies are advised to enhance employee engagement and cultivate a collaborative work environment to attain sustained competitive advantage in the context of Industry 4.0.
Value engineering analysis of the green semesta housing project in Semarang Faza, Muhammad Arief; Antonius, Antonius; Wibowo, Kartono
International Journal of Mechanical Computational and Manufacturing Research Vol. 13 No. 4 (2025): February: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/computational.v13i4.226

Abstract

The demand for housing continues to rise along with the growing population. Housing development is one of the efforts to meet society's need for residential homes. The Green Semesta housing project in Semarang offers Type 36 and Type 45 houses. However, given the vast area of Semarang and the intense competition among housing developers offering higher-segment housing at similar price ranges, it can be concluded that there is cost inefficiency in the construction of this project. Therefore, a solution is needed to address this issue by applying Value Engineering. This study aims to analyze the optimization of the cost budget plan without compromising the quality and functionality of the buildings using the Value Engineering method.This method compares the cost advantages of the landscape design before and after redesign by modifying the house layout, appearance, and the number and composition of houses/site plans to achieve maximum benefits. This analysis follows the stages of Value Engineering Planning, which include the information stage, creative stage, analysis stage, recommendation stage, and presentation stage. Based on the results of the Value Engineering analysis of the Green Semesta Housing Project in Semarang, the most profitable design alternative is Design B, which involves modifying the number of Type 45 units from 21 to 9 and increasing the Type 36 units from 16 to 31. After the redesign, the production cost for Type 45 units decreased from IDR 135,254,167.70 to IDR 124,656,875,91, while the original cost for Type 36 units decreased from IDR 96,224,877.00 to IDR 93,086,166.00.

Page 8 of 10 | Total Record : 95

 6   7   8   9   10 

Filter by Year

2020 2025


Reset
Filter By Issues
All Issue 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