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Andi Adriansyah
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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
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Positioning of quality systems in lean manufacturing: integrated approach vs independent implementation in the food industry Sitorus, Helena; Budianto, Budianto; Feri, Zefki Okta; Nurlaila, Qomarotun; Suryatman, Tina Hernawati; Fitra, Fitra
SINERGI Vol 29, No 3 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.3.013

Abstract

Despite the widespread adoption of Lean Manufacturing (LM), its effectiveness in the food industry remains underexplored, particularly regarding the integration of the Quality System (QS). The purpose of this research is to compare QS placement and LM implementation strategies in the food industry. This study utilized a comparative approach, analyzing empirical data from four food processing companies in Indonesia over six months, employing qualitative methods (expert interviews, document analysis) and quantitative analysis. Response Surface Methodology (RSM) with the Box-Behnken design was applied for optimization, while Principal Component Analysis (PCA) identified key variables influencing Lean Manufacturing success. Two implementation strategies were compared: phased implementation with a separate Quality System (Companies A and B) and simultaneous implementation with an integrated Quality System (Companies C and D). The findings revealed that Company A achieved the highest performance, with 88% in 5S and 85% in Just-In-Time (JIT), followed by Company B with 80% in JIT and 75% in 5S. In contrast, companies C and D exhibited lower performance. PCA results indicated that PC1 (80.40%) was associated with on-time delivery and sales growth, whereas PC2 (14.47%) was linked to rejection factors. Companies A and B excelled in PC1, while Companies C and D were more dominant in PC2. These findings suggest that phased implementation of LM tools is more effective than simultaneous application. This research not only addresses a critical gap in the literature but also provides practical insights for food industry practitioners seeking to enhance operational efficiency through Lean Manufacturing.
Car seatbelt monitoring system using real-time object detection algorithm under low-light and bright-light conditions Suryanto, Agus; Wicaksono, Dwi Haryo; Mulwinda, Anggraini; Harlanu, Muhammad; Syah, Mario Norman
SINERGI Vol 29, No 3 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.3.018

Abstract

Seatbelt usage is essential for minimizing injury risk during vehicular accidents. The monitoring seatbelt system in modern vehicles can be easily tricked into not displaying the warning alert. Car seatbelt detection, utilising real-time object detection, is employed to monitor seatbelt usage. However, the accuracy of such systems needs to be further evaluated under low-light and bright-light conditions. This study aims to develop a car seatbelt monitoring system using a real-time object detection algorithm, which will be tested in low-light and bright-light scenarios. The system integrates a trained YOLOv5 model into embedded hardware, which interfaces directly with the vehicle’s ignition system, enabling or disabling engine start based on seatbelt usage. Notifications are also delivered through LEDs, a buzzer, and Telegram messages. This system has an accuracy of 95.75%, precision of 99.1%, recall of 96.2%, and an F1-score of 97.2%. The results show that the system can generate a better confidence score under bright-light conditions than under low-light conditions. This work offers tangible proof of the efficacy of applying intelligent object detection models for real-time driver monitoring, particularly in enhancing compliance through physical intervention and IoT-based alerts.
An FFT-based vibration characterization on road profile of two-wheeler electric vehicle Firmansyah, Mohamad Ardy; Feriyanto, Dafit; Firdaus, Himma; Pranoto, Hadi; Istiqomah, Istiqomah
SINERGI Vol 29, No 3 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.3.023

Abstract

Vibration is an inevitable physical phenomenon; excessive and uncontrolled amounts of vibration can result in damage and system failure. In accordance with various automotive product certification standards, vehicle batteries or rechargeable electrical energy stotrage system (REESS) must undergo a vibration test to assess their mechanical integrity. This study aims to broaden the perspective on vibration assessment by examining it during vehicle operation and assessing the protective capabilities of vehicle suspension against vibrations from damaged roads in two-wheeled electric motor vehicles. The proposed method involves installing an accelerometer on the battery pack body placed in the battery compartment. The experimental setup involved conducting tests on a 125-meter track, with the vehicle traversing roads characterized by concrete cracks, uneven surfaces, and potholes. Two distinct speed variations were selected for analysis: 10 and 15 kilometers per hour. The results obtained from the Rion VA 12 portable vibration analyzer are presented as a plot of the fast Fourier transform (FFT) graph. The maximum acceleration recorded was 2.35 and 1.98 G at the same frequency of 7 hertz (Hz). This research method and result aligns with others, including those focused on assessing road damage, passenger comfort, and vehicle component damage, such as shock absorbers. In the future, the development of a vehicle battery support structure is anticipated to further minimize vibration disturbance by reducing the peak acceleration values depicted in the FFT graph. The minimization of incoming vibrations is expected to enhance the safety and durability of the battery pack. 
Spatial components in social interaction spaces: a review of Jakarta urban kampongs dwellers Anggiani, Mona; Arifin, Lilianny Sigit; Dwisusanto, Yohanes Basuki
SINERGI Vol 29, No 3 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.3.014

Abstract

Architecture exists because of the response to the needs of human social relationships. Space is one part of architecture that is very important for use in everyday human life, one of which is social interaction space. Urban kampongs are settlements in Jakarta that contain social interaction space for dwellers. This space is an important space and is often discussed in the scope of architecture, but there has been no special review of the aspects that form the social interaction space used by dwellers of urban kampongs in Jakarta. Therefore, it is important to conduct a special study that discusses the aspects that form the social interaction space in urban kampongs. This study is a literature study that uses a qualitative method with a narrative descriptive analysis approach. The basic literature used is an understanding of spaces from the perspective of sociology, anthropology, and geography. The results of the study show that the social interaction space of dwellers of urban kampongs in Jakarta is greatly influenced by non-physical aspects (socio-cultural) and physical aspects (location). This study is very useful for enriching the theory regarding the social interaction space of urban kampongs in particular and the theory of spatial design in general. 
Optimizing intrusion detection with data balancing and feature selection techniques Elsi, Zulhipni Reno Saputra; Supli, Ahmad Affandi; Jimmie, Jimmie; Al-Faris, Muhammad Ghozi; Rapel, David Agustianto
SINERGI Vol 29, No 3 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.3.019

Abstract

The rapid growth of IoT devices has brought significant security challenges, particularly in detecting various types of attacks within heterogeneous network environments. This study explores the effectiveness of data balancing techniques, including Random Undersampling (RUS), Cost-Sensitive Learning (CSL), Synthetic Minority Oversampling Technique (SMOTE), and Randomized Combination Sampling (RCS). Feature selection methods, namely correlation (threshold 0.8) and mutual information (top 15 features), were employed to optimize feature sets. The Decision Tree (DT) and Linear Discriminant Analysis (LDA) classifiers were used to evaluate the performance of balanced datasets. The evaluation metrics included accuracy, precision, recall, F1-score, G-mean, and ROC curves. The results revealed that SMOTE and RCS outperformed other balancing methods, with SMOTE achieving the highest accuracy (98.7%) and RCS demonstrating robust G-mean values across both feature selection techniques. DT consistently showed better performance compared to LDA across all metrics, while feature selection significantly improved the classification results, particularly under mutual information criteria. However, the analysis highlighted limitations of LDA in handling imbalanced datasets and high-dimensional features. This study concludes that a combination of advanced data balancing and effective feature selection significantly enhances the accuracy of intrusion detection in IoT networks. Future work will focus on integrating real-time detection systems and exploring hybrid models to further improve the detection of complex attacks in dynamic IoT environments. 
Experimental investigation of the Moment Bolted Coupler (MBT) with steel on the bond strength under different monotonic pull-out tests Mohamad Nor, Mohamad Amir; Ahmad, Nursafarina; Mansor, Hazrina
SINERGI Vol 29, No 3 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.3.025

Abstract

The bond strength between steel reinforcement bars and mechanical bolted couplers (MBT) is essential for the structural integrity of reinforced concrete structures. However, various pull-out test methods yield inconsistent results when assessing this bond strength. This research examines the impact of reinforcement bar diameter (12mm, 16mm, and 20mm) and three different pull-out test configurations (M1, M2, and M3) on the bond strength of MBT couplers. The M1 method, employing direct tensile loading and a standard clamp zone, consistently produced the highest bond strength values across all bar diameters. Its simplicity, reliability, and adherence to standardized procedures make it the preferred method for determining the maximum bond capacity of MBTs. While the M2 and M3 methods offer insights into coupler behavior under complex loading scenarios, they exhibit lower bond strength values compared to M1. The M1 pull-out test method is recommended as the primary method for evaluating the bond strength of MBT in practical applications, with M2 testing as a potential supplement for a more comprehensive understanding of coupler behavior.
Experimental study and optimisation of flexural properties of 3D-printed polylactic acid for energy-storing-and-returning prosthetic foot Suteja, The Jaya; Handoko, Rico; Soesanti, Arum
SINERGI Vol 29, No 3 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.3.015

Abstract

A prosthetic foot with energy-storing-and-returning capabilities requires high strength to prevent damage, high rigidity for stability, and low weight for user comfort. Therefore, efforts are needed to optimise the properties of the 3D-printed prosthetic foot. Based on the literature review, a research gap remains in understanding the complex interactions among 3D printing parameters that improve flexural properties, minimise mass, and reduce printing time. This study investigated how infill density, layer thickness, shell thickness, and their interaction affect the flexural strength-to-mass ratio, flexural modulus of elasticity, strain, and required printing time of the 3D-printed product. The experimental parameter ranges are infill density (40–60%), layer thickness (0.2–0.3 mm), and shell thickness (0.8–1.6 mm). A case study was conducted to optimise these parameters using the Response Surface Methodology with the Box-Behnken Design. The experimental data were fitted to a quadratic model, and Analysis of Variance determined the significance of individual factors. A gradient-based algorithm then identified the optimal parameter combinations. Results indicated that shell thickness was the most influential factor on the flexural strength-to-mass ratio and flexural modulus. Additionally, the interaction between layer height and shell thickness significantly affected strain, while infill density impacted printing time. The optimal values obtained were 32.5722 MPa/gram for the flexural strength-to-mass ratio, 2727.06 MPa for the modulus, 0.0522 for the strain, and 757.7788 seconds for the printing time. The novelty of this research lies in presenting how the interaction between shell thickness, layer thickness, and infill density affects process productivity and material efficiency while preserving product performance.
Risk-based predictive maintenance of medium voltage network switching equipment using analytical hierarchy process as an analytical tool Gumilang, Erick Satriyo; Hudaya, Chairul; Sudiarto, Budi; Husnayain, Faiz
SINERGI Vol 30, No 1 (2026)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2026.1.011

Abstract

Predictive maintenance has become crucial for enhancing the reliability and efficiency of electrical systems, especially for Medium Voltage Network (MVN) switching equipment, which plays a key role in electricity distribution. This study aimed to develop a risk-based predictive maintenance model for MVN switching equipment using the Analytical Hierarchy Process (AHP) for maintenance prioritization, along with Z-score and Monte Carlo simulation methods to evaluate risk likelihood and impact. The Z-score method assessed the probability of risks occurring, revealing a probability exceeding 90% for specific equipment, such as UP2D.2025.C4, at 93.12%. The Monte Carlo simulation assessed the potential impact of these risks, showing severe consequences for various types of equipment. For example, UP2D.2025.C1 had a mean of 28.51 and a standard deviation of 3.50, while UP2D.2025.C8 had a standard deviation of 33.17, with an impact of over 61.53%. AHP was used to assign priority weights to components based on criteria such as equipment age, operational condition, and failure history. The analysis indicated that the Lightning Arrester had the highest maintenance priority at 26.04%, followed by the Fuse Cutout at 20.62% and the Pole-Mounted Circuit Breaker at 11.15%. This research was expected to significantly contribute to the development of more efficient and effective maintenance strategies for electrical systems, particularly in the electricity distribution sector.
Real-time Unmanned Surface Robot (USR) for river quality monitoring systemm Mohd Aras, Mohd Shahrieel; Ponusamy, Pavitrah; Md Nawawi, Mohamad Riduwan; Zohedi, Fauzal Naim; Bahar, Mohd Bazli; Abdullah, Lokman; Khamis, Alias; Rizman, Zairi Ismael
SINERGI Vol 30, No 1 (2026)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2026.1.001

Abstract

A real-time Unmanned Surface Robot (USR) for river water quality monitoring system is a technology that employs a small autonomous boat outfitted with sensors and other monitoring equipment to gather and transmit data on various water quality parameters like pH, temperature and total dissolved solids sensors in rivers and other bodies of water. The USR can traverse the river, gather information or data at specific points or designated locations, as well as continuously monitor a specific stretch of river at all times. The data or information was sent in real time to a central monitoring station, where it was analyzed and used to identify potential water quality problems. Initially, the USR was designed using SolidWorks software, and its structural performance was the main focus of the investigation and examination of the design.  This USR was then created and manufactured.  The entire USR system could help detect and mitigate pollution and other environmental problems, as well as offer useful information for managing water resources. Next, to determine the overall performance of the USR, five experiments and autopilot accuracy tests were performed. Finally, this study also verified and validated the accuracy of water quality monitoring sensors. 
3D numerical investigation of roadway bridge response under hydrodynamic forces and local scour in stiff clay and sand foundations Saiful Nizam, Nurul Shafrina Atika; Ahmad, Nordila; Suif, Zuliziana; Jelani, Jestin
SINERGI Vol 30, No 1 (2026)
Publisher : Universitas Mercu Buana

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

Abstract

Bridges are critical components of transportation networks but are highly vulnerable to failure during extreme flood events, particularly due to hydrodynamic forces and local scour. This study quantitatively evaluates the effects of flood velocity and scour depth on bridge pier displacement for two representative soil conditions: very stiff clay (Ground Type B) and medium-dense sand (Ground Type C). A 3D finite-element model incorporating non-linear p–y springs was developed in CSI Bridge to represent soil–structure interaction (SSI). A total of 192 simulations were performed across flood velocities of 2–16 m/s and scour depths ranging from 0DF to 2DF. The results show that pier displacement increases systematically with both velocity and scour, with medium-dense sand exhibiting up to 30% higher displacement than very stiff clay at severe flood conditions (0.07 m vs. 0.06 m). These findings highlight the importance of soil stiffness in governing pier response under extreme hydrodynamic loading. While the study does not address debris impact, flow directionality or additional hydraulic parameters, the outcomes provide valuable insight for improving foundation design and incorporating SSI considerations into flood-resilient bridge engineering.

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