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
 46   47   48   49   50 
Verification of a 3-Degree-of-freedom Bus Handling Model Due to Steering Wheel Input Hakima, Muhammad Akhmal; Aparowa, Vimal Rau; Abd Kadir, Zulkiffli; Sakundarini, Novita; Hudha, Khisbullah; Amer, Noor Hafizah
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.022

Abstract

This paper discusses about the development and modeling of a 3-DOF (Degrees of Freedom) bus handling model in response to steering wheel input from the driver. It includes all the relevant mathematical equations. The handling model was created using MATLAB/Simulink, incorporating parameters from TruckSim data to accurately represent the bus. The simulation results were verified by comparing them with TruckSim responses from two test procedures namely double lane change and single lane change tests. The comparison focuses on trends, magnitudes and percentage differences between the developed model and TruckSim results. In the double-lane change test, the largest percentage difference observed was 7%, while the smallest was 0.5% for yaw rate and longitudinal acceleration, respectively. In the single-lane change test, the largest percentage difference was 7.27% for lateral acceleration, and the smallest was 1.5% for yaw rate. The verification indicates that the simulation model closely aligns with TruckSim trends and can be effectively used for further study of bus dynamics in various scenarios.
Evaluation of double-stage Anaerobic Fluidized Bed Reactor (AFBR) for digestion of leachate: correlation of kinetic parameter with operational condition and process Prastyo, Elli; Budhijanto, Wiratni; Sudibyo, Hanifrahmawan
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.013

Abstract

The objective of this study is to investigate the performance of using an advanced fluidized bed reactor (AFBR) of a double column configuration in breaking down leachate into biogas. The relationship of the kinetic parameters with the operating conditions and the performance of the double-column reactor during anaerobic digestion was examined. The substrate concentration, microorganism population, hydraulic retention time value, growth rate, and death rate of microorganisms were employed as reference points for evaluating anaerobic digestion performance and assessing the operating conditions. The results demonstrated that there was no notable correlation between the formation of volatile fatty acids (VFA) in the acidogenic reactor (R1), the degradation of VFA in the methanogen reactor (R2), and the methane production rate in the methanogen reactor (R2). The simulation results for VFA formation (dCVFA1/dt) and VFA degradation (dcVFA2/dt) exhibited a tendency to overestimate when operated at low HRT and underestimate at short HRT compared to the experimental results. The steady state of the simulation results exhibited a faster rate of progression than the experimental outcomes. The fitting data for Ksx1 and Ksx2 predominantly comprise dynamically evolving values that exert an influence upon um1 and um1, as well as kd1 and kd2, when the reactor is operated in continuous mode. Furthermore, the factors of inhibitor compounds and microorganism adaptation were not observed across all HRT values in this investigation. 
Comparative study of CNN techniques for tuberculosis detection using chest X-ray images from Indonesia Dwijayanti, Suci; Agam, Regan; Suprapto, Bhakti Yudho
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.018

Abstract

Convolutional neural networks (CNNs) represent a popular deep-learning approach for image classification tasks. They have been extensively employed in studies aimed at classifying tuberculosis (TB), coronavirus disease 2019 (COVID-19), and normal conditions on chest X-ray images. However, there is limited research utilizing Indonesian data, and the integration of CNN models into user-friendly interfaces accessible to healthcare professionals remains uncommon. This study addresses these gaps by employing three CNN architectures—AlexNet, LeNet, and a modified model—to classify TB, COVID-19, and normal condition images. Training data were sourced from both a local hospital in Indonesia (RSUP dr. Rivai Abdullah) and an additional online dataset. Results indicate that AlexNet achieved the highest accuracy, with rates of 97.52%, 64.45%, and 92.43% on the Kaggle dataset, the RSUP Dr. Rivai Abdullah dataset, and the combined dataset, respectively. Subsequently, this model was integrated into a user interface and deployed for testing using new data from the RSUP Dr. Rivai Abdullah dataset. The web-based interface, powered by the Gradio library, successfully detected 7 out of 10 new cases with 70% accuracy. This implementation may enable medical professionals to make preliminary diagnoses.
Reduced graphene oxide-ZnO hollow microsphere composite for supercapacitor applications Abdullah, Abqari Luthfi Albert; Radiman, Shahidan; Chiu, Wee Siong; Abdul Hamid, Muhammad Azmi; Badrudin, Fadhlul Wafi
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.023

Abstract

Through a facile solvothermal synthesis process, a reduced graphene oxide-ZnO microsphere composite was produced at 180 °C for 24 hours. Raman spectroscopy, X-ray diffraction, field emission scanning electron microscopy, and transmission electron microscopy were used to analyze the morphological structures of the material. The analysis revealed that hexagonal phase wurtzite ZnO nanoparticles assembled homogeneous microspheres, decorated on the graphene sheets by graphene oxide functional groups. The ZnO nanoparticles are about 30 nm in size and the microspheres are hollow. A possible growth mechanism for the formation of ZnO hollow microspheres anchored on graphene sheets has been proposed. Cyclic voltammetry, galvanostatic charge-discharge and electrochemical impedance were used to evaluate the electrochemical performance of the composite. At a scan rate of 1 mV/s, the reduced graphene oxide-ZnO hollow microsphere composite electrode demonstrated an enhanced specific capacitance of 40.70 F/g with energy and power densities of 5.75 Wh/kg and 1.97 kW/kg, respectively.
Identifying degradation pathways at Sembrong Dam, Johor: insights from Sentinel-2 satellite imagery and NDVI analysis Anjang Ahmad, Mustafa; Kahlid, Muhammad Dzikri; Mohd Hussin, Muhammad Haziq Izzuddin; Mohammad Razi, Mohd Adib; Hussein Al-Qadami, Ebrahim Hamid; Cahyadi, Mokhamad Nur
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.014

Abstract

The study is to evaluate the catchment area mapping at Sembrong Dam in Johor, Malaysia and identify potential transit pathways contributing to dam water degradation while implementing targeted mitigation works. The analysis involved the surface runoff patterns and topographical/geographic data via a digital elevation model (DEM), providing insights into terrain characteristics, slope, and flow directions to hydrological dynamics that significantly contribute to water resource management. This study focuses on producing the catchment area map with satellite imagery and defining the transit pathway that potentially causes water degradation in a reservoir. The analysis uses satellite images from sentinel-2 processing to generate a detailed runoff map and DEM of the catchment area surrounding the dam. The study uses Red Bands (RED) and Near-Infrared Bands (NIR) to process sentinel satellite images to create NDVI maps. Data is uploaded as Raster data in QGIS, and NDVI calculations are performed to transform raw satellite data into an index for vegetation health. NDVI values are classified into different colour classes to visualize the condition of the study area. High NDVI values indicate higher concentrations of agriculture nutrients, potentially triggering eutrophication in watersheds through surface runoff. The study analyzed a 66.89 km2 reservoir catchment area using runoff maps. NDVI analysis showed vegetation density and plant health, with robust vegetation in the dam-surrounded region with an NDVI value of 0.8. However, due to its narrow geography and deep lakes, the northeastern region is slightly polluted and susceptible to algae growth. The study aims to improve understanding of LULC and water conditions by analyzing pollution levels using remote sensing data, DEM, and NDVI for mitigation strategies.
Acoustic and visual optimization in the configuration of exhibition space partitioning Kristianto, Thomas Ari; Ekasiwi, Sri Nastiti Nugrahani; Arifianto, Dhany
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.019

Abstract

For museum and other exhibition designers, partitions are a crucial element in showcasing exhibition content. The massive partitions also serve to aid the acoustic performance of the space, by isolating the audio content. allowing visitors to better hear the audio content. On the other hand, designers tend to design pavilion spaces for maximum visual connectivity while considering circulation and space efficiency. This research examines the acoustic performance of three commonly used partition models to determine the relationship between partition openness and their respective acoustic environments. This research uses mixed methods to capture the instrumentalizing and perceptual aspects of humans.  The objective method uses a digital raytracing simulation and impulse response tests in a 1:1 scale space model. This method describes the sound wave distribution and acoustic performance of a space in terms of several parameters. Conversely, the intersubjective method involved surveying 60 respondents to understand visitors’ perceptions of focus, distraction, and acoustic comfort within the pavilion space. The study demonstrates that a pavilion design with side partitions around 120 cm wide achieves the most optimum performance compared to designs with 240 cm side height partitions or no partitions. Furthermore, the research highlights the acoustic characteristics of the three fundamental pavilion models. These findings can inform people about the development of more tailored and versatile pavilion designs. 
Experimental study of rainfall intensity on silty sand slope Jelani, Jestin; Suif, Zuliziana; Ahmad, Nordila; Muhammad Sadiq Rabbani, Muhammad Jazil Rabbani; Khairulazman, Nurul Afiffah
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.024

Abstract

Malaysia, located in the tropical region, is blessed with an abundance of rainfall, particularly during the monsoon season. Previous studies have shown that major landslide occurrences in Malaysia are primarily caused by frequent and prolonged rainfall. This study is conducted to investigate the effect of different rainfall intensities on the silty sandy slope through a small-scale slope model. The soil samples were collected from Bukit Tabur, Kuala Lumpur, Malaysia, to construct a 60° slope model. A continuous rainfall intensity of 50, 100, and 150 mm/hour was considered in the study to determine the type and duration of failure. Two cameras were positioned at the front and side of the slope model to capture the elapsed time since the onset of rainfall. The gullies failures were observed in all experiments. It is due to the soil on the slope surface reaching nearly full saturation, causing runoff water to move down the slope and drain downstream, resulting in surface erosion. Such a failure mechanism agreed well with the failures (formed gullies) recorded on the downstream slope of the Bukit Tabor after high-intensity rainfalls. The time of failure for different rainfall intensities was compared to the highest rainfall intensity. The duration of slope failure for 50 mm/hr and 100 mm/hr is approximately 30% and 5% slower than that of rainfall intensity at 150 mm/hr. The results suggest that the slope is more prone to failure with higher rainfall intensities. 
Real-time dental caries segmentation with an efficient Deformable U-Net (DU-Net) for teledentistry system Iklima, Zendi; Kadarina, Trie Maya; Salamah, Ketty Siti; Sentosa, Arrival Dwi
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.015

Abstract

Digital technology has greatly improved teledentistry by facilitating telediagnostics and teleconsultations, particularly benefiting those in remote areas. Additionally, AI advancements enhance diagnostic accuracy and streamline clinical decision-making, reducing costs and resource disparities in dental care. This study presents an improved U-Net architecture, Deformable U-Net (DU-Net), for semantic dental caries segmentation, leveraging deformable convolutions to dynamically adjust sampling points for improved feature extraction and reduced computational redundancy. By connecting encoder-decoder blocks via skip-connections, the DU-Net architecture enables efficient real-time segmentation and balance accuracy while reducing computational demands. The deformable block in DU-Net and DDR U-Net shows a balanced performance and efficiency while maintaining accuracy despite reduced FLOPs. The proposed architecture was implemented in real-time dental caries segmentation on a Dual Core Cortex A72 system and web server. It shows a significant improvement in Dice score, reducing CPU and memory usage compared to conventional U-Net models. Moreover, the DU-Net and its half variants achieved competitive performance with much lower computational demands makes suitable for web servers and embedded applications. The result highlights the DU-Net capability to optimize both computational efficiency and segmentation accuracy, offering a promising solution for real-world applications where speed and resource management are critical, particularly in the medical imaging field.
Cikakembang River Restoration from the Perspective of Numerical Modelling Kent, Steven; Yudianto, Doddi; Gao, Cheng; Fitriana, Finna; Wang, Qian
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.020

Abstract

The poor condition of the Citarum River demands more significant pollution control. One alternative for controlling pollution can be limiting the amount of wastewater entering one of the tributaries of the Citarum River, namely the Cikakembang River. This study is a follow-up study that will model heavy metal parameters in the Cikakembang River. Data collection was carried out six times, where the heavy metal parameter detected was copper. Numerical modelling for copper parameters was carried out using MATLAB software with the Runge Kutte-4 discretisation scheme. The study location covers 2.36 km upstream of the Cikakembang River, with 12 textile industry wastewater disposal points. Numerical modelling results for copper parameters show a settling rate of heavy metal particles of 40 day-1, with a maximum RRMSE value of 9.97%. Combining the water quality models for organic and heavy metal parameters created, pollution control simulations can be run in both seasons. The pollution control scenario aims to find the maximum amount that enters the Cikakembang River without passing the class four river water quality standards. The selection of the standard is based on the use of Cikakembang River water, namely for irrigation purposes. Based on the results of pollution control simulations, the pollutant carrying capacity for BOD, COD and copper parameters in the Cikakembang River is 199.43 kg/day, 1103.80 kg/day and 4.06 kg/day, respectively.
Optimizing PSO for classification: comparison of Naïve Bayes and C4.5 for osteoporosis prediction Anugerahwati, Zulfi; Lestari, Sri
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.011

Abstract

Osteoporosis is a medical disease marked by a reduction in bone density, which significantly increases the risk of fractures. Osteoporosis patients do not always exhibit symptoms and because current diagnostic techniques have limitations, early detection is frequently needed. The osteoporosis dataset consists of 1.958 records each containing 15 regular attributes and 1 special attribute as the label.  The attribute represented as “1” for the presence of osteoporosis and “0” for its absence. The primary objective is to predict an individual’s risk of developing osteoporosis, including age, gender, bone density, lifestyle factor, medical history, and nutritional intake of calcium and vitamin D. To achieve this, Naïve Bayes and C4.5 has been employed. PSO is employed to identify the most relevant features, thereby optimizing the efficiency and accuracy of the classification models. The initial step in data preprocessing involved handling missing values to ensure data integrity. After implementing PSO, Naïve bayes improved from 82,65% to 83,67%, while C4.5 exhibited an even greater increase, rising from 91,07% to 96,17%. PSO significantly optimizes model, with the most improvement in C4.5. PSO proves to be a valuable tool for feature selection. Age and Hormonal Change emerged as important for both models. Furthermore, Physical Activity and Calcium Intake, which despite having varying levels of influence, were consistently considered relevant.  By focusing on these significant attributes, enables us more effectively monitor and recognize early signs of osteoporosis. Identifying individuals at high risk, more effective early detection and intervention, improving the potential for timely management and prevention.

Page 48 of 54 | Total Record : 531

 46   47   48   49   50 

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