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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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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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Service quality dealer identification: the optimization of K-Means clustering Yolanda Enza Wella; Okfalisa Okfalisa; Fitri Insani; Faisal Saeed; Ab Razak Che Hussin
SINERGI Vol 27, No 3 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.3.014

Abstract

Service quality and customer satisfaction directly influence company branding, reputation and customer loyalty. As a liaison between producers and consumers, dealers must preserve valuable consumer relationships to increase customer satisfaction and adherence. Lack of comprehensive measurement and standardization regarding service quality emerges as a consideration issue towards the company service excellence. Therefore, identifying the service quality performance and grouping develops into valuable contributions in decision-making to control and enhance the company's intention. This study applies the K-Means Algorithm by optimizing the number of clusters in identifying dealer service quality performance. Hence, the ultimate service quality formation will be performed. The analysis found three dealer identification categories, including Cluster One, with 125 dealers grouped as good performance; Cluster Two, with 30 dealers grouped as very good performance; and Cluster Three, with 38 dealers grouped as not good performance. In order to evaluate the efficacy of optimum k value, the lists of testing approaches are conducted and compared, whereby Calinski-Harabasz, Elbow, Silhouette Score, and Davies-Bouldin Index (DBI) contribute in k=3. As a result, the optimum clusters are determined through the highest performance of k values as three. These three clusters have successfully identified the service quality level of dealers effectively and administered the company guidelines for corrective actions and improvements in customer service quality instead of the standardized normal distribution grouping calculation. 
Project managers competency on project performance of green toll road development project in Indonesia Mairizal Mairizal; Rahmat Alifiardi; Gilang Ardi Pratama; Mohd Zaimi Abd Majid; Shek Poi Ngian
SINERGI Vol 27, No 3 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.3.005

Abstract

The Green Road Construction development program is a program that has the potential to reduce carbon emissions from road construction. Currently, the Government of the Republic of Indonesia through the Ministry of Public Works and Public Housing together with the Toll Road Business Entity continues to strive to provide the best service to the community using Toll Roads that are applied to all Toll Roads in Indonesia, especially Green Toll Roads. At the implementation stage, it has not been able to run smoothly because there are several constraining factors such as social and environmental aspects. For this reason, this study aims to find out what factors are needed by a Project Manager who carries out the construction. References are taken from various journals and articles that discuss green toll roads around the world and in Indonesia. This research is a combination of qualitative and quantitative (mixed methods) by distributing questionnaires to several respondents. The results of the factor analysis show that the Project Performance factor (Y) is strongly influenced by the determinant factors namely Knowledge (X1) in terms of Time (X1.3), Cost (X1.4) and Procurement (X1.7). Henceforth, project performance (Y) is also influenced by Knowledge (X1), Skill (X2), and Tools & Techniques (X3). Meanwhile, on the other hand, the Project Performance factor (Y) is also influenced by the Green Toll Road (Z). 
The impacts of 5D-Building Information Modeling on construction's Time and cost performance Hedy Herdyana; Agus Suroso
SINERGI Vol 27, No 3 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.3.010

Abstract

The construction sector is essential to a country's economic growth and development. This is why the construction of building projects is one of the most pressing concerns for the Indonesian government. The industrial sector has become increasingly dynamic and responsive to the challenges of building projects due to technological advancements. One example is the Building Information Modelling (BIM) 5D, an emerging technology integrating project implementation time and costs into a 3D model. Therefore, this study aims to investigate the success factors of BIM 5D implementation on the time and cost performance of high-rise building construction projects at Campus-II UIN Sunan Ampel Surabaya. This was achieved through a quantitative research method using a questionnaire completed by 62 respondents: the project manager, site manager, engineering head, and site engineer. Moreover, descriptive statistics were utilized to examine the frequency distribution of concentration measures and data distribution on sample characteristics and variables. The findings showed that the factors of tender document, human resources, BIM software, planning process and production process simultaneously positively affected the construction project's cost and time performance.
A review towards Friction Stir Welding technique: working principle and process parameters Rikko Putra Youlia; Diah Utami; Dedik Romahadi; Yang Xiawei
SINERGI Vol 27, No 3 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.3.001

Abstract

Friction Stir Welding (FSW) is a solid-state bonding process that employes tools that are not used up and can function to connect two opposite workpieces without melting the workpiece material. The friction force has been micro-structurally tested to reformat or transform the inner state of the structure properties (atomic formation) form in metal since the kinetic energy of friction has been utilised in one of the welding techniques. Right afterwards, the studies reported that the mechanical properties also underwent a significant deformation. The aim is to determine the effect of Welding Procedure Specification (WPS) product quality. As it develops through research and applied experiments, the branch of friction-based welding discipline can be classified depending on how the friction mechanism can produce the finest solid-state joint, which is suitable to the typical property of metal and can be maximised by joint configuration. Friction Stir Welding is a friction-based welding technique that uses the stirring tool to generate friction while the workpieces are stuck on the line of the FSW joint configuration. The relevant correlations amongst process parameters and inside its respective adjustable variables are constructed to the finest principles that produced top-grades empirical reports of the weld properties. In this review, the explanation of the working principle and clarification of process parameters are presented. The cited references are selected from creditable and verifiable articles and books in the last ten years. Expectedly, it will be able to pioneer a new face of simple and understandable review articles.
Good Manufacturing Practice (GMP) in Tofu MSMEs in North Aceh Cut Ita Erliana; Iskandar Hasanuddin; Yuwaldi Away; Raja Ariffin Raja Ghazilla
SINERGI Vol 27, No 3 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.3.015

Abstract

This study examined tofu MSMEs in Lhokseumawe City and the North Aceh District. Observations indicate discrepancies between tofu production and the GMP requirements for Good Manufacturing Practices. The amount that the tofu sector has adopted appropriate food production procedures by the Regulation of the Ministry of Sector of the Republic of Indonesia Number 75/M-IND/PER/7/2010 is determined using a GMP approach. This research is anticipated to improve the product safety of the tofu industry and provide recommendations for improvement. In this study, data collection techniques included candid interviews related to the GMP aspect questionnaire consisting of 11 inspection aspects, direct field observation of 21 MSMEs by marking the location conditions, production equipment, and materials used, and following the processing process, followed by a search for deviations from GMP aspects and comparison with the literature review, documentation of the necessary data related to GMP assessment, and a search for relevant literature. According to the evaluation, 12 MSMEs with a value range of 41% to 60% fell into the category of not meeting the requirements. The second criterion is extremely inadequate, ranging from 21% to 40% for five MSMEs. Additionally, the criteria for sufficient completion with a range of values between 61% and 80% for up to 4 MSMEs led to an evaluation of 11 GMP aspects in 21 MSMEs. Know on the location aspect with a percentage of 71% in the sufficient category, building aspects with a percentage of 11% in the critical category, aspects of sanitation with a percentage of 40% in the category of very less fulfilling, aspects of machinery and equipment with a percentage of 80% in the category of sufficiently fulfilling, aspects of materials with a percentage of 100% in the category of fulfilling, and aspects of supervision with a percentage of 40% in the category of fulfilling.
Image Segmentation in Aerial Imagery: A Review Ade Purwanto; Dewi Habsari Budiarti; Fithri Nur Purnamastuti; Irfansyah Yudhi Tanasa; Yomi Guno; Aris Surya Yunata; Mukti Wibowo; Asyaraf Hidayat; Dede Dirgahayu
SINERGI Vol 27, No 3 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.3.006

Abstract

The problem of distinguishing objects has plagued researchers for many years because of low accuracy compared to human eyes’ capability. In the last decade, the use of Machine Learning in aerial imagery data processing has multiplied, with the technology behind it has also developed exponentially. One of those technologies is image-based object identification, which relies heavily upon data computation. To reduce the computational load, various data segmentation algorithm was developed. This study is focused on reviewing the various image segmentation technology in aerial imagery for image recognition. Literature from as far as 1981 from various journals and conferences worldwide was reviewed. This review examines specific research questions to analyze image segmentation research over time and the challenges researchers face with each method. Machine Learning has gained popularity among segmentation methods. However, Deep Learning has been aggressively put an essential role in it by overcoming many of its weaknesses. The advanced algorithm used in Deep Learning to process the segmentation may drive more efficient and accurate data processing. 
Application of Capacity Spectrum Method (CSM) for non-symmetrical reinforced concrete high-rise buildings as a tool for seismic design Ayuddin, Ayuddin; Bindhu, K. R.
SINERGI Vol 27, No 3 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.3.011

Abstract

The development of earthquake resistance design of structures in the last decade has been critically changing from strength and ductility to performance criteria, where the structure is decided for various levels of structural performance. To understand the structural performance because, at time, a large earthquake load on the structure will experience structural yielding, non-linear analysis with the capacity spectrum method will be performed. The relationship between roof displacement and base shear force is described by a curve that describes the structural capacity is a capacity curve. To determine the behavior of the structures under review for a given earthquake intensity, the capacity curve is then compared with the performance demand based on various earthquake intensities. The results of the case studies for reinforced concrete portals non-symmetrical 3D concluded that the convergence obtained at the point of the structure performance is   and . The displacement results for the actual structure () were 286.71 mm and building base shear coefficient was 15.46 %.
Optimization of Ultra-Wideband bandwidth for the design of microstrip monopole antennas using Defected Ground Structure and star-shaped patche Muhammad Darsono; Muhammad Rega
SINERGI Vol 27, No 3 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.3.002

Abstract

This paper presents a design of a monopole microstrip antenna developed to support Ultra-wideband (3.1 -10.6 GHz) technology wireless communication systems. An antenna with minimalist dimensions operates on C-Band (wireless LAN) and X-Band (downlink satellite) frequencies. The antenna profile has a star shape patch on the top side and the use of the Defected Ground Structure (DGS) technique on the bottom side on RT DUROID substrate media. The design uses a simulation method using software and measurement tests on antenna prototypes to obtain parameters and antenna performance characteristics. The results of the measurement test, the bandwidth return loss < -10 dB has a difference of 40% (absolute) and 0.7% (Fractional) lower than the simulation when VSWR < 2. The radiation pattern forms an omnidirectional with a maximum directivity (Gain) of 5.18dBi with polarization vertical. Overall, the UWB monopole antenna design results have a low profile, compact, small size, and support mobile communication devices.
Optimized Swarm Enabled Deep Learning Technique for Bone Tumor Detection using Histopathological Image Dama Anand; Osamah Ibrahim Khalaf; Fahima Hajjej; Wing-Keung Wong; Shin-Hung Pan; Gogineni Rajesh Chandra
SINERGI Vol 27, No 3 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.3.016

Abstract

Cancer subjugates a community that lacks proper care. It remains apparent that research studies enhance novel benchmarks in developing a computer-assisted tool for prognosis in radiology yet an indication of illness detection should be recognized by the pathologist. In bone cancer (BC), Identification of malignancy out of the BC’s histopathological image (HI) remains difficult because of the intricate structure of the bone tissue (BTe) specimen. This study proffers a new approach to diagnosing BC by feature extraction alongside classification employing deep learning frameworks. In this, the input is processed and segmented by Tsallis Entropy for noise elimination, image rescaling, and smoothening. The features are excerpted employing Efficient Net-based Convolutional Neural Network (CNN) Feature Extraction. ROI extraction will be employed to enhance the precise detection of atypical portions surrounding the affected area. Next, for classifying the accurate spotting and for grading the BTe as typical and a typical employing augmented XGBoost alongside Whale optimization (WOA). HIs gathering out of prevailing scales patients is acquired alongside texture characteristics of such images remaining employed for training and testing the Neural Network (NN). These classification outcomes exhibit that NN possesses a hit ratio of 99.48 percent while this occurs in BT classification.
Design of water level detection monitoring system using fusion sensor based on Internet of Things (IoT) Andi Adriansyah; Muhammad Hanif Budiutomo; Heri Hermawan; Reni Ika Andriani; Rama Sulistyawan; Abu Ubaidah Shamsudin
SINERGI Vol 28, No 1 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2024.1.019

Abstract

River flooding is a condition when the water in a river overflows and exceeds its normal capacity, thereby flooding the surrounding area. This flood disaster has been a known problem for a long time and causes great damage in the affected areas. Flood events inRivers are influenced by many factors, such as climate change, rapid urbanization, inappropriate land use, ineffective water management patterns, as well as uncontrolled addition of hard soil surfaces. Flood conditions in rivers involve complex processes and are influenced by various factors components, such as rainfall, water flow, topography, vegetation, and many other factors. Therefore, this research is very urgent because it can help reduce the negative impacts of flooding, increase public safety, become a basis for decision making, save costs and resources and make a positive contribution to technological development. This study aims to create a prototype of a flood early warning system. The system is based on a wireless sensor network whose interconnections are connected by a star topology. Every node is a combination of several sensors (sensor fusion) that are related to detecting floods, such as: height sensors, water flow speed sensors and rainfall intensity sensors. Design of hardware (hardware) and software (software) will be done. A classification mechanism based on Fuzzy Logic will be used to estimate flood conditions based on existing data. Flood estimation will determine the time and distance of flood events that will occur. Several experiments in the laboratory will be carried out to determine the performance of the designed system.

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