cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Andi Adriansyah
Contact Email
andi@mercubuana.ac.id
Phone
+628111884220
Journal Mail Official
sinergi@mercubuana.ac.id
Editorial Address
Fakultas Teknik Universitas Mercu Buana Jl. Raya Meruya Selatan, Kembangan, Jakarta 11650 Tlp./Fax: +62215871335
Location
Kota adm. jakarta barat,
Dki jakarta
INDONESIA
Sinergi
Published by Universitas Mercu Buana
ISSN : 14102331     EISSN : 24601217     DOI : https://dx.doi.org/10.22441/sinergi
Core Subject : Engineering,
Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering
SINERGI is a peer-reviewed international journal published three times a year in February, June, and October. The journal is published by Faculty of Engineering, Universitas Mercu Buana. Each publication contains articles comprising high quality theoretical and empirical original research papers, review papers, and literature reviews that are closely related to the fields of Engineering (Mechanical, Electrical, Industrial, Civil, and Architecture). The theme of the paper is focused on new industrial applications and energy development that synergize with global, green and sustainable technologies. The journal registered in the CrossRef system with Digital Object Identifier (DOI). The journal has been indexed by Google Scholar, DOAJ, BASE, and EBSCO.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 531 Documents
 42   43   44   45   46 
Blockchain-BIM: reducing cost in green retrofitting for sustainable construction development Husin, Albert Eddy; Kristiyanto, Kristiyanto; Kussumardianadewi, Bernadette Detty
SINERGI Vol 28, No 3 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2024.3.009

Abstract

During the implementation process, the construction sector significantly affects the environment, leading to environmental pollution and the overconsumption of natural resources. This jeopardizes the sustainability of a healthy living environment, requiring a solid system to control development. A sustainable and environmentally friendly development system is crucial from architectural, construction, and economic perspectives. However, when applying the concept of Green Building to existing buildings, the cost of green retrofits has increased by about 10.77%. A case study was carried out on the existing BRIN (National Research and Innovation Agency) building to provide alternative solutions to reduce these green retrofitting costs, making sustainable construction the primary option in developing the construction sector. One way to address this cost increase is using the Blockchain-Building Information Modeling (BIM) application, an alternative method to determine the most economical cost based on input or a given model. BIM models contain non-geometric information, including materials for building components, quantities, prices, procedures, scales, and sizes. This allows for real-time data exchange and collaborative decision-making between stakeholders, improving visualization and modeling and lowering costs due to better construction outcomes and higher productivity probability. The implementation of Blockchain-BIM is expected to result in green retrofit cost savings of at least 3% on each green level according to the Ministry of Public Works and Housing (PUPR) of the Republic of Indonesia Technical Guidelines No. 01/SE/M/2022, namely Primary, Intermediate, and Main.
A systematic review of geopolymer materials: innovations, prevailing constraints and resolutions Agashua, Lucia Omolayo; Arum, Chinwuba; Oluyemi-Ayibiowu, Bamitale Dorcas; Ikumapayi, Catherine Mayowa
SINERGI Vol 28, No 3 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2024.3.004

Abstract

Geopolymer is a novel eco-friendly biodegradable cementitious material for which the emergence is expected to reduce the carbon-dioxide emission caused by Portland cement manufacturing companies. Geopolymer material possesses exceptional mechanical properties and other admirable properties such as fire and corrosion resistance. Most industrial solid wastes (ISW) and waste smoldering bottom ash (WSBA) are stacked up, filling land mass, besides their harmful influence on the surroundings. Reprocessing could make them suitable for use as materials for making geopolymers. They can efficiently adsorb heavy metals, dyes or pigments, and other radioactive contaminants, which is very helpful to humanity's future development. On the other hand, due to the exceptional features of geopolymer material, its functions go further than that. Specific helpful information regarding geopolymer materials was made known in this study. The study encompassed the source of geopolymer materials, the geopolymerization process, the categories of activators, their formation techniques, and the diverse usage areas of geopolymer materials. Furthermore, the factors influencing the mechanical features of geopolymer materials were discussed. Finally, these materials' inadequacies and usage precincts were summarized, and their evolution was abridged to prepare a theoretical or hypothetical base for the lasting improvement of geopolymer materials.
Optimization of preventive maintenance on critical machines at the Sabiz 1 plant using Reliability-Centered Maintenance method Cahyati, Sally; Puspa, Sofia Debi; Himawan, Riswanda; Agtirey, Novan Rojabil; Leo, Joseph Andrew
SINERGI Vol 28, No 2 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2024.2.015

Abstract

Maintenance planning is the first step in an industry, especially when it comes to the trade-off between cost and reliability, which is the reason for this research's aim. The Reliability Centered Maintenance (RCM) method will be used in this research to optimize maintenance activity in critical machines at the Sabiz 1 plant to minimize downtime, costs incurred for machine repairs, and production losses. The tools of RCM that will be used such as FMEA to determine critical machines as the focus of analysis, a Fishbone Diagram to determine the causes of failure, an RCM worksheet to get preventive activities, and a statistical distribution approach to obtain appropriate preventive activity intervals. The result of data processing shows that all data has a lognormal distribution and can be continued using the lognormal distribution method. The results of this analysis are the preventive maintenance activities proposal and their intervals as a reference for Sabiz 1 plant maintenance planning. The preventive maintenance plan for three critical machines is the high-pressure pump is four days of inspection activities and two days for replacement activities; for the powder, base conveyor is four days of checking activities and 17 days for replacement activities; and for the extraction tower fan for inspection, activities is seven days. The prediction of the implementation impact of this maintenance planning will save maintenance costs around 70% compared to historical costs.
Experimental investigation on slope runoff, sediment, and hydraulic parameters under different underlying surface Hamizak, Siti Norhafizah; Suif, Zuliziana; Jelani, Jestin; Ahmad, Nordila; Akhtar, Muhammad Izzul
SINERGI Vol 29, No 1 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.1.023

Abstract

This study utilizes a rainfall simulator to conduct an experimental investigation of slope and rainfall on various underlying surfaces. This study aimed to determine the relationship between various hydraulic factors and sediment concentration by estimating runoff, sediment concentration generation, and hydraulic parameters on various underlying surfaces. The flow velocity, flow depth, shear stress, and unit stream power are the hydraulic parameters in this experiment. The soil sample will be set up appropriately in the rainfall simulator with a slope of 20º and subjected to a rainfall event for two hours on four trays with various underlying surface types. The rainfall intensity of 10 Lmin⁻¹ was designated for the rainfall simulator. Throughout a two-hour period, the runoff flow was collected at intervals of 30, 60, 90, and 120 minutes. The measured sediment concentration using Total Suspended Solid (TSS). Then measurements were conducted of the sediment concentration, runoff discharge, and hydraulic parameters. According to the results, the stream power of the four covers is higher for the dried leaves (0.004606 ms-3), grass cover (0.003274 ms-3), gravel (0.00232 ms-³), and bare soil cover (0.00081 ms-³). But bare soil produces the maximum concentration of sediment and surface runoff, which is then followed by grass, gravel, and leaves. In general, the generation of sediment began with the bare surface, gravel, dry leaves, and grass in descending sequence. Research has shown that rain-induced plant cover can be used as a low-cost strategy to reduce soil erosion on construction slope sites. 
Improved recommender system using Neural Network Collaborative Filtering (NNCF) for E-commerce cosmetic product Subhan, Subhan; Syarif, Deny Lukman; Widhihastuti, Endah; Rakainsa, Senda Kartika; Sam'an, Muhammad; Ifriza, Yahya Nur
SINERGI Vol 29, No 1 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.1.014

Abstract

This study presents an enhanced recommender system tailored for e-commerce platforms specializing in cosmetic products. Traditional recommender systems often need help providing accurate and personalized recommendations due to the complexity and subjectivity inherent in cosmetic preferences. In e-commerce, personalized product recommendations are crucial to improving user engagement and driving sales. This paper presents an innovative approach to enhance recommendation systems by leveraging neural network collaborative filtering techniques for the cosmetic product domain. The proposed method integrates neural networks into collaborative filtering, namely neural network collaborative filtering with improved preprocessing step. To validate the effectiveness of our proposed system, extensive experiments were conducted using real-world e-commerce cosmetic datasets "eCommerce Event History in Cosmetics Shop".   Additionally, we evaluate the system's performance using historical e-commerce event data in cosmetics stores, demonstrating the system's effectiveness with mean reciprocal ratings (MRR) and normalized discount cumulative gain (NDCG). Evaluation Metrics of MRR and NDCG in this study got 0.56 and 0.60, respectively, with a split of the data: 70% train data, 15% validation data, and 15% test data. This study obtained better evaluation metrics than the previous study, which had an MRR of 0.31 and NDGC of 0.32. Furthermore, this model exhibits robustness against data sparsity and cold-start problems commonly encountered in e-commerce platforms. This research advances knowledge of recommendation systems and paves the way for more personalized and efficient online shopping experiences.
Effect of curing temperature on the soil physical and mechanical properties on clay shale geopolymer fly ash stabilization Hartono, Edi; Diana, Willis; Muntohar, Agus Setyo; Azhar, Muhammad; Indriani, Lia
SINERGI Vol 29, No 1 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.1.005

Abstract

Clay shale is an easily degraded mudrock when exposed to weathering. The reduced strength due to degradation can be mitigated through soil stabilization. In recent years, soil stabilization using geopolymers has become one of the latest popular methods due to its economic benefits and lower carbon footprint. A widely used cementitious material for this method is fly ash-based geopolymer. The relationship between curing temperatures and the performance of clay shale stabilized with fly ash-based geopolymer has yet to be studied for the purpose of identifying a more effective stabilization method. In this study, clay shale was stabilized using geopolymer. The geopolymer was made of fly ash and an activator. Sodium hydroxide (NaOH) and sodium silicate (Na2SiO3) as activators. The activator is diluted with water to create a 12 M mixture. Before the unconfined compressive strength test, the specimens were subjected to various curing temperatures from 26oC to 60oC. The test result shows that, in general, higher curing temperatures increased the dry density from 1.66 g/cm3 to 1.84 g/cm3. Meanwhile, the unconfined compressive strength multiplies about 3.5 times. Furthermore, the moisture content decreased after the curing process from 19% to 2.5%. This led to the specimen volume experiencing decrement due to the shrinkage during the curing period. The volume reduces from 67.7 cm3 to 63.5 cm3. In general, temperature plays a significant role in enhancing the strength of clay shale stabilized using fly ash-based geopolymer.
Classification of palm oil fruit ripeness based on AlexNet deep Convolutional Neural Network Kurniawan, Rudi; Samsuryadi, Samsuryadi; Mohamad, Fatma Susilawati; Wijaya, Harma Oktafia Lingga; Santoso, Budi
SINERGI Vol 29, No 1 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.1.019

Abstract

The palm oil industry faces significant challenges in accurately classifying fruit ripeness, which is crucial for optimizing yield, quality, and profitability. Manual methods are slow and prone to errors, leading to inefficiencies and increased costs. Deep Learning, particularly the AlexNet architecture, has succeeded in image classification tasks and offers a promising solution. This study explores the implementation of AlexNet to improve the efficiency and accuracy of palm oil fruit maturity classification, thereby reducing costs and production time. We employed a dataset of 1500 images of palm oil fruits, meticulously categorized into three classes: raw, ripe, and rotten. The experimental setup involved training AlexNet and comparing its performance with a conventional Convolutional Neural Network (CNN). The results demonstrated that AlexNet significantly outperforms the traditional CNN, achieving a validation loss of 0.0261 and an accuracy of 0.9962, compared to the CNN's validation loss of 0.0377 and accuracy of 0.9925. Furthermore, AlexNet achieved superior precision, recall, and F-1 scores, each reaching 0.99, while the CNN scores were 0.98. These findings suggest that adopting AlexNet can enhance the palm oil industry's operational efficiency and product quality. The improved classification accuracy ensures that fruits are harvested at optimal ripeness, leading to better oil yield and quality. Reducing classification errors and manual labor can also lead to substantial cost savings and increased profitability. This study underscores the potential of advanced deep learning models like AlexNet in revolutionizing agricultural practices and improving industrial outcomes.
Effect of building designation on parking characteristics, road performance, and zoning regulation da Costa, Don Gaspar Noesaku; Suni, Yulius P. K.
SINERGI Vol 29, No 1 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.1.010

Abstract

If the capacity of the parking zone on buildings with great trip attractiveness rates is inadequate, it usually triggers on-street parking activity and its unintended derived impacts. Unfortunately, although this unintended situation may decrease traffic and road environmental quality, a similar situation always occurs. The initial field observation's result indicates that a change in building utilization may have influenced it. So, this study aims to assess the effect of parking accumulation rates due to a change in building utilization on the parking index and its impacts on road performance, including traffic accident risk. The existing parking index is influenced by parking accumulation and capacity, while the planning parking index is determined by comparing the parking accumulation and standardized parking space. In addition, the effect of on-street and road performance was assessed using results from similar previous studies. It was found that a change in building function significantly impacts the existing parking index value. It could not accommodate the increased trip rate, resulting in on-street parking activity. It influences a decrease in road capacity, travel speed, air pollutants, and sight distance (increasing accident risk level). This indicates that an institutional strengthening capability represented in an appropriate zoning regulation, which describes the type, number, and scale of activities allowed to be built in a particular corridor, is a compulsory requirement. Consequently, the ladder of urban land use planning should be re-reviewed. Implementing this new concept should be considered, especially in an urban fast-growth corridor. 
Design of 3 DOF hexapod leg movement using inverse kinematics: bridging gaps in multilegged robot kinematics literature Suwoyo, Heru; Taufikurohman, Nur Aziz; Tian, Yingzhong; Burhanudin, Achmad
SINERGI Vol 29, No 1 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.1.001

Abstract

Designing the motion of a hexapod robot with 3 Degrees of Freedom (DOF) using the Inverse Kinematics method allows the robot to move by adjusting the angles of its leg joints according to the desired position and direction. This research involves the geometric and structural design of the hexapod robot and the development of an Inverse Kinematics algorithm to calculate the leg joint angles based on the target pose. The study uses the Inverse Kinematics method to design a hexapod robot for movement with 3 DOF. The testing results show an average Inverse Kinematics error of 1.56 mm on the X-axis, 0.88 mm on the Y-axis, and 0.78 mm on the Z-axis. During the forward and backward movement tests covering a distance of 100 cm, the average error was 2.58 cm and 12.38 cm, respectively. For the rotation tests, the average error was 3.6° for a 90° rotation to the right, 3° for a 90° rotation to the left, 13.2° for a 180° rotation to the right, and 3.8° for a 180° rotation to the left. The results indicate that the design of the 3DOF hexapod robot using the Inverse Kinematics method provides a sufficient level of accuracy in controlling movements along the X, Y, and Z axes. Despite some errors, the robot is capable of moving fairly accurately during forward, backward, and rotational movements.
Mineralogical analysis of plutonic and volcanic rocks at selected slope sections of the Kuala Lumpur-Karak Highway Khairulazman, Nurul Afiffah; Jelani, Jestin; Suif, Zuliziana; Umor, Mohd Rozi; Azmi, Nur Anati; Md Yusof, Zainuddin; Ahmad, Nordila; Abd Halim, Abd Akram Haikal; Rosle, Qalam A’zad
SINERGI Vol 29, No 1 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.1.024

Abstract

The Kuala Lumpur-Karak Highway (KL-KH) is a key route connecting Kuala Lumpur to the East Coast states of Peninsular Malaysia. It passes through three distinct geological formations: the Kuala Lumpur Granite, Genting Sempah Complex, and Bentong Raub Suture Zone. These formations feature unique rock mineral compositions and microstructures that influence the strength and behavior of rock masses. This study used X-ray Diffraction (XRD) and Scanning Electron Microscopy (SEM) to analyze the mineralogical properties of plutonic and volcanic rock samples from the highway. The plutonic sample from KM29 (GKM29) consists of quartz, muscovite, and albite, while the volcanic sample from KM93 (LKM93) is rhyolite, containing quartz, albite, muscovite, and biotite. While both samples share similar minerals, they differ in texture, mineral proportions, and carbon content. The GKM29 sample has a more granular texture, while the LKM93 sample is finer. These differences in mineral composition and texture affect the mechanical properties of the rocks, including strength and durability, which are crucial for slope stability. Understanding these variations is essential for assessing slope stability and potential geological hazards along the highway. This study emphasizes the importance of early geological assessments for effective slope management and road safety, enabling better planning and maintenance strategies.

Page 44 of 54 | Total Record : 531

 42   43   44   45   46 

Filter by Year

2013 2026


Reset
Filter By Issues
All Issue Vol 30, No 1 (2026) Vol 29, No 3 (2025) Vol 29, No 2 (2025) Vol 29, No 1 (2025) Vol 28, No 3 (2024) Vol 28, No 2 (2024) Vol 28, No 1 (2024) Vol 27, No 3 (2023) Vol 27, No 2 (2023) Vol 27, No 1 (2023) Vol 26, No 3 (2022) Vol 26, No 2 (2022) Vol 26, No 1 (2022) Vol 25, No 3 (2021) Vol 25, No 2 (2021) Vol 25, No 1 (2021) Vol 24, No 3 (2020) Vol 24, No 2 (2020) Vol 24, No 1 (2020) Vol 23, No 3 (2019) Vol 23, No 2 (2019) Vol 23, No 1 (2019) Vol 22, No 3 (2018) Vol 22, No 2 (2018) Vol 22, No 1 (2018) Vol 21, No 3 (2017) Vol 21, No 2 (2017) Vol 21, No 1 (2017) Vol 20, No 3 (2016) Vol 20, No 2 (2016) Vol 20, No 1 (2016) Vol 19, No 3 (2015) Vol 19, No 2 (2015) Vol 19, No 1 (2015) Vol 18, No 3 (2014) Vol 18, No 2 (2014) Vol 18, No 1 (2014) Vol 17, No 3 (2013) More Issue