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Andi Adriansyah
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Fakultas Teknik Universitas Mercu Buana Jl. Raya Meruya Selatan, Kembangan, Jakarta 11650 Tlp./Fax: +62215871335
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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
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Evaluation of the Performance of Corroded Concrete with Bottom Ash and Bacteria using Resistivity and Impact Echo Techniques Zaki, Ahmad; Azizah, Salma; P. Rosyidi, Sri Atmaja; Mahbubi, Khairil; Ibrahim, Zainah
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.003

Abstract

Concrete is a significant contributor to global emissions, necessitating the development of environmentally friendly alternatives. This study explores the use of reinforced concrete (RC) incorporating industrial by-products, specifically bottom ash (BA), as a partial sand replacement to address this issue. Additionally, the study examines the potential of Bacillus subtilis bacteria to enhance the self-repair capabilities of corroded RC with BA. Concrete mixtures with 10%, 20%, and 30% BA were prepared and subjected to accelerated corrosion for 48, 96, and 168 hours. The corroded RC specimens were then tested for compressive strength, flexural strength, corrosion rate, non-destructive testing (NDT) methods, and SEM analysis. NDT methods included impact echo (IE) and resistivity techniques. Results showed that increasing BA content led to a decrease in corrosion resistance, with current measurements of 2.07, 1.64, and 1.47 amperes for 10%, 20%, and 30% BA, respectively. After 168 hours of corrosion, the IE frequency of the Bacillus subtilis-treated specimens was 2561.04 Hz, the lowest among all samples, while the 30% BA specimen exhibited the highest frequency at 7924.81 Hz. Resistivity measurements after 168 hours showed lower resistivity in Bacillus subtilis-treated specimens (18.25 kΩ·cm) compared to the 20% BA specimen (29.27 kΩ·cm). These findings suggest that the addition of BA and Bacillus subtilis bacteria can reduce the corrosion risk in concrete, making it a viable alternative to traditional RC.
Assessment of revetment performance against wave overtopping for mitigating tidal flooding at Lebih Beach Eryani, I Gusti Agung Putu; Andin, Ni Nyoman Yulleta; Armaeni, Ni Komang; Araújo, Odilia Belija Do Carmo; Jayantari, Made Widya
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.008

Abstract

As one of the largest archipelagic nations, Indonesia faces significant coastal erosion challenges, particularly in Gianyar Regency, Bali, where coastline change rates have reached -11.12 m/year. To combat this issue, the Indonesian government has implemented revetment structures along the coastline, notably at Lebih Beach. This research systematically assesses the current performance of a coastal revetment structure on Lebih Beach, focusing on its ability to withstand modern wave conditions and prevent wave overtopping. The objective is to evaluate the structure’s physical integrity and functionality, especially as wave overtopping has impacted nearby communities and damaged infrastructure. The methodological framework incorporates detailed field surveys to document structural conditions and detect signs of erosion, material degradation, or damage. Topographic and bathymetric data are used to model the coastal and seabed profile, which is essential for simulating wave behavior. Wind, tide, and wave data from CMS-Wave in SMS 10.1 software provide insights into wave height, direction, and energy, helping predict wave impacts on each segment of the coastline. The research area is divided into six segments along the Lebih Beach coastline. Initial evaluations showed that segments 1 through 4 require further analysis due to evident vulnerabilities to wave forces. The reexamination compares the peak elevation of these segments, specifically their ability to withstand wave action at the established elevation of +5.00 m. This comparison allows for an accurate assessment of the structure’s resilience under current environmental pressures and guides recommendations for maintenance or reinforcement where needed. The evaluation results in segments 1, 2, 3, and 4 showed that the revetment still undergoes overtopping. Continuous monitoring and evaluation of coastal protection structures is needed to ensure the integrity of coastal communities and infrastructure in the face of ongoing environmental changes.
Evaluating the impact of autonomous material handling on the performance of production system: a simulation approach Purwaningsih, Ratna; Shintyastuti, Annisa Rahma; Arvianto, Ary; Hapsari, Chaterine Alvina Prima; Putri, Ade Aisyah Arifna; Dzulfikar, Rifki Daris
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.004

Abstract

In developing countries, low employment rates lead to manual material handling due to low labor costs. This article analyzes the impact of transitioning from semi-manual to fully automatic material handling systems by replacing the hand pallet system with AGV for transporting materials on the production floor. A simulation model was created to evaluate the impact of the transition on cost and quality. The model focuses on production lines with predetermined pathways and fixed working hours for workstations. The discrete event simulation was developed using ExtendSim. Queuing theory model is employed to assess the utilization of resources within the system. Three scenarios are developed: a human system, systems with 2 AGVs, and 3 AGVs.The findings suggest that systems with AGVs surpass human-operated systems in terms of system reliability, cost-effectiveness, and product excellence. The findings provide essential insights for management decision-making, specifically for deterministic production lines. The research findings emphasize the possibility of significant enhancements in production system performance by implementing autonomous material handling.
Investigation of mechanical properties and microstructural characteristics of rice husk ash-based geopolymer mortar as patch repair Astuti, Pinta; Isnaini, Muhammad Sakti; Sasmita, Devi; Purnama, Adhitya Yoga; Habirun, Asiya Nurhasanah; Zulkarnain, Anisa; Nouvaldi, Angga Jordi; Monika, Fanny
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.009

Abstract

The rapid expansion of the construction sector has escalated cement use, significantly impacting the environment due to CO2 emissions. Geopolymers are eco-friendly construction materials designed to reduce cement use and have the potential to be a patching material to rehabilitate concrete structures due to corrosion damage. Among these, pozzolanic materials like rice husk ash, rich in aluminosilicate, are abundant and suitable for geopolymer binders. This study explored the use of rice husk ash and alkali activators (NaOH/Na2SiO3), with different activator percentages (40%, 45%, and 50%), to evaluate their mechanical properties and potential applications as patch repair materials. This research involved formulating an optimal mix design through trial and error in a laboratory setting, followed by curing at 70 °C and testing at room temperature. XRF and SEM-EXD analyses were performed to determine the chemical composition and microstructure of the specimens. The activators, NaOH and Na2SiO3, were employed in a 1:3.5 ratio, with 14M molarity and 2% superplasticizer, to enhance workability. The test yielded the geopolymer mortar’s highest compressive strength of 8.14 MPa at a 40% activator variation. In comparison, the highest split tensile and flexural strengths were 2.50 MPa and 1.00 MPa, respectively, both at a 50% variation. These findings demonstrated the suitability of the mortar for patch repair on concrete substrates with compressive strengths below 8 MPa. The mechanical properties of the rice husk ash geopolymer mortar were influenced by the silica, calcium, and alkali activator content, affecting the mortar’s strength and density.
Bibliometric analysis of research trends in rigid pavement over the last decade Mudjanarko, Sri Wiwoho; Paikun, Paikun; Daniel, Basil David
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.005

Abstract

This study presents a bibliometric analysis of research trends in rigid pavement over the last decade, aiming to identify publication trends, research output distribution, main themes, citation patterns, and research gaps. The PRISMA method was employed, and statistical analysis was conducted using bibliometric software. By collecting bibliographic data from academic publications, this research reveals a significant growth in rigid pavement publications, reflecting increased global interest in this field. Major research themes include pavement design, material characterization, construction techniques, maintenance, and performance evaluation. Citation pattern analysis is used to identify influential works in this field. However, this study has limitations in data coverage and is susceptible to biases inherent in bibliometric analysis. Nevertheless, it contributes significantly to understanding the research landscape of rigid pavement, providing valuable insights for researchers, practitioners, and policymakers. Future research could deepen qualitative analysis, track the evolution of research themes, and explore interdisciplinary frameworks to enrich our understanding of rigid pavements.
High-performance sentiment classification of product reviews using GPU(parallel)-optimized ensembled methods Rao, Annaluri Sreenivasa; Reddy, Yeruva Jaipal; Navya, Guggilam; Gurrapu, Neelima; Jeevan, Jala; Sridhar, M.; Reddy, Desidi Narasimha; Pathuri, Siva Kumar; Anand, Dama
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.010

Abstract

Sentiment analysis is an important approach in natural language processing (NLP) that extracts information from text to infer underlying emotions or views. This technique entails classifying textual information into feelings like "positive," "negative," or "neutral." By evaluating data and labeling, client input may be classified on scales such as "good," "better," "best," or "bad," "worse," resulting in a sentiment classification. With the fast expansion of the World Wide Web, a massive library of user-generated data—opinions, thoughts, and reviews—has evolved, notably for diverse items. E-commerce firms use this data to gather attitudes and views from social media sites like Facebook, Twitter, Amazon, and Flipkart. The GPU-CUDA-ENSEMBLED algorithm is a GPU-accelerated method for sentiment classification, enhancing predictive performance by minimizing variances and biases. It outperforms existing algorithms like SLIQ and MMDBM, demonstrating GPU mining's efficiency. The proposed algorithm utilizes GPU-accelerated sentiment analysis to accurately predict smartphone ratings, providing valuable insights for businesses to maximize customer feedback potential.
Performance of speech enhancement models in video conferences: DeepFilterNet3 and RNNoise Maulana, Muhammad Iqbal; Raisul Akbar, Muhammad Fadhlillah; Iklima, Zendi
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.001

Abstract

As remote work and online education continue to gain prominence, the importance of clear audio communication becomes crucial. Deep Learning-based Speech Enhancement has emerged as a promising solution for processing data in noisy environments. In this study, we conducted an in-depth analysis of two speech enhancement models, RNNoise and DeepFilterNet3, selected for their respective strengths. DeepFilterNet3 leverages time-frequency masking with a Complex Mask filter, while RNNoise employs Recurrent Neural Networks with lower complexity. The performance evaluation in training revealed that RNNoise demonstrated impressive denoising capabilities, achieving low loss values, while DeepFilterNet3 showed superior generalization. Specifically, "DeepFilterNet3 (Pre-Trained)" exhibited the best overall performance, excelling in intelligibility and speech quality. RNNoise also performed well in subjective quality measures. Furthermore, we assessed the real-time processing efficiency of both models. Both RNNoise variants processed speech signals almost in real-time, whereas DeepFilterNet3, though slightly slower, remained efficient. The findings demonstrate significant improvements in speech quality, with "DeepFilterNet3 (Pre-Trained)" emerging as the top-performing model. The implications of this study have the potential to enhance video conference experiences and contribute to the improvement of remote work and online education.
The effect of using Ground Granulated Blast Furnace Slag (GGBFS) in mortar mixes on setting time Irawan, Dafid; Priyandoko, Gigih; Moreira Loe, Febriana Dominggas; Ayuningtyas, Firda Hani
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.021

Abstract

This study highlights the potential of GGBFS as an additive to speed up cement hydration, improve cement durability, and lessen the environmental impact of more widely used cement. This study aims to analyze the effect of varying percentages of GGBFS on the setting time of mortar. We chose GGBFS as an additive because of its environmentally friendly properties and its efficiency in enhancing the mechanical characteristics of mortar. This study uses an experimental method with variations in the GGBFS composition of 0%, 10%, 20%, and 30%. We conducted laboratory tests using a Vicat apparatus on 12 samples to measure the initial and final setting times and analyze the slump value. The research results show that the addition of GGBFS significantly affects the setting time of the mortar. A GGBFS composition of 10% resulted in the fastest initial setting time (145 minutes) and the fastest final setting time (245 minutes), compared to the control without GGBFS. (215 menit dan 315 menit). Slump testing indicates that GGBFS reduces the slump value by up to 20% (8.7 cm) but increases at a 30% composition. (11.3 cm). ANOVA analysis shows a significant effect with a calculated F-value (12.14) greater than the F-table (4.07).
Flood and landslide exposure awareness for mitigation of road network performance: a community-based approach Rifai, Andri Irfan; Prasetijo, Joewono; Isradi, Muhammad; Sari, Yusra Aulia; Zolkepli, Muhammad Farhan
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.012

Abstract

Natural disasters in the form of floods and erosion in remote area road networks pose challenges for the government. The involvement of community-based disaster management can make it easier for stakeholders to carry out disaster mitigation intelligently. Digital technology can provide information about disaster conditions and facilitate coordination between related parties in managing floods and landslides. This research aims to explore the cultural understanding of the local community to encourage community-based involvement in optimizing road infrastructure services that have been disrupted due to floods and landslides. This qualitative research method uses data from surveys, Focus Group Discussions (FGD), and in-depth interviews. Several community leaders, non-government organizations, and the government became sources of data and discussions. The research results are divided into four main results: 1) Based on exploring the cultural understanding of the local community about disasters, the community is very concerned about road safety and accessibility. Communities in the road network area have also understood the causes of floods and landslides that can disrupt road functions; 2) Culturally, the community is accustomed to and actively involved in disaster preparedness; 3) Hereditarily, the community has been an essential part of the disaster mitigation process; 4) The community feels comfortable using social media platforms to accelerate community communication in disaster mitigation and handling.
A Bidirectional-RRT*-Connect-Assisted RRT*-Smart for a path planning algorithm Suwoyo, Heru; Hastomi, Yudi; Andika, Julpri
SINERGI Vol 29, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.2.017

Abstract

Although Rapidly Exploring Random Tree Star (RRT*) has been considered to be able to achieve convergence to an optimal solution, this method has a slow convergence speed and requires an infinite amount of time to produce a truly optimal solution. For this reason, RRT*-Smart which includes path optimization and intelligent sampling processes was introduced. Although the addition of these methods can directly complete infinite-duration RRT* searches, they will work once the initial path obtained with RRT* is available. The effectiveness of reducing the optimality time is determined by the initial path formed. If this path is not close to optimal, the path optimization and intelligent sampling process will take a long time, and vice-versa. For this reason, RRT*-Connect, which has the advantage of searching from two directions, is proposed in this study. The goal is to replace the RRT* algorithm to produce a more optimal initial formed path. Based on this approach, this method will be named Connect-RRT*-Smart. Several methods, such as RRT, RRT*, RRT*-Connect, and RRT*-Smart, are compared to see their performance in producing the feasible path. Regarding this comparative result, the proposed method shows better performance in terms of convergence speed and path optimality. 

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