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 22 Documents
 1   2   3 
Search results for , issue "Vol 28, No 2 (2024)" : 22 Documents clear
The use of Fuzzy Logic Controller and Artificial Bee Colony for optimizing adaptive SVSF in robot localization algorithm Suwoyo, Heru; Hajar, Muhammad Hafizd Ibnu; Indriyanti, Prastika; Febriandirza, Arafat
SINERGI Vol 28, No 2 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2024.2.003

Abstract

The objective of solving feature-based localization problems is to estimate the path of the robot referring to a given map. Thus, it is not surprising that robust estimators such as Smooth Variable Structure Filter (SVSF) are often used to handle this problem. Basically, its use is highly dependent on an accurate system model and known statistical noise. Where neither of these are available by definition. Therefore, the conventional way is not recommended and the use of an adaptive filter approach can be involved. Based on this and although only partially, Innovation Adaptive Estimation (IAE) has been considered to have a positive influence on improving the performance of the estimator. But not infrequently the solutions offered by this approach also lead to divergences due to unmapped dynamic conditions. Moreover, in this proposal, IAE is enhanced by applying Artificial Bee Colony-Tuned Fuzzy Logic. The hope is that there is quality control for the process noise covariance Q and R measurements by updating them based on the output of this ABC-Tuned FLC.
Intelligent system design for identification of unbalance and misalignment using Fuzzy Logic methods Romahadi, Dedik; Feriyanto, Dafit; Anggara, Fajar; Wijaya, Fathoni Putra; Dong, Wang
SINERGI Vol 28, No 2 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2024.2.004

Abstract

Vibration analysis identifies emerging vibration problems before they become unmanageable and cause unforeseen delays. This can be accomplished by monitoring engine vibration continuously or at specific intervals. Unbalance is a common vibration issue caused by the center of mass shifting from the center of rotation, leading to misalignment and excessive vibration between shafts. To prevent this, manual monitoring is required, but it is time-consuming. Therefore, intelligent system monitoring is necessary to save time. Using a large amount of vibration, spectrum, and phase data as input, this project aims to develop a diagnostic application for motor problems based on vibration signals. Fuzzy logic is implemented in MATLAB software to process a considerable amount of input data for all vibrations, spectrums, and phases using the fuzzy logic method. A vibration meter is used to collect vibration data from the demonstration machine. All input data will be processed by the fuzzy system based on predefined fuzzy rules that must provide accurate results for the actual operating conditions of the demonstration machine. Conducting experiments will help the intelligent system correctly detect damage from misalignment and imbalance. The intelligent fuzzy logic system can accurately diagnose damage caused by misalignment and unbalance on the demonstration machine.
A simplified dental caries segmentation using Half U-Net for a teledentistry system Kadarina, Trie Maya; Iklima, Zendi; Priambodo, Rinto; Riandini, Riandini; Wardhani, Rika Novita; Setiowati, Sulis; Jusoh, Mohd Taufik
SINERGI Vol 28, No 2 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2024.2.005

Abstract

High-reliability diagnostic equipment efficiently supported by a computer-based diagnostics system. For instance, a computational approach establishes a model that can diagnose diseases. Artificial intelligence has been applied to aid in the field of medical imaging. Classification, prediction, and localisation of lesions or dental caries greatly minimise the load and difficulties for clinical practitioners. In this study, U-Net architectures are simplified to propose the feature reduction of the decoder layers. This simplification of U-Net architectures is utilised for segmented dental caries images. This paper simplified the U-Net decoder layers into the level of blocks Half-UNet () and Half-UNet (). The Half-UNet structural model surpasses the U-shaped structural model in terms of efficiency and segmentation capabilities. The simplification of the UNet architecture outperformed using Half-UNet 0.83% of the dice coefficient. The Half-UNet design is able to preserve model performance in segmenting actual images and ground truth against expected ground truth.
Production of bio-coal based on empty fruit bunches by torrefaction method with fixed bed and tubular continuous reactors Martin, Awaludin; Ginting, Yogie Rinaldy; Kurniawan, Iwan; Agusta, Dhiky Rahman; Khotimah, Nur
SINERGI Vol 28, No 2 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2024.2.006

Abstract

Excessive use of fossil energy has negative impacts, which can cause climate change and environmental degradation. Thus, there is a need to find alternative, more sustainable energy sources. Biomass derived from Empty Fruit Bunch (EFB) waste is a newfound renewable energy source. However, its utilization is not optimal due to its low heating value and high chlorine (Cl) and potassium (K) content, which can interfere with combustion. EFB is washed with peat water to reduce potassium and chlorine content, and the torefaction process is used for combustion. This research aims to develop bio-coal production from empty fruit bunches using the torefaction method using fixed beds and continuous tubular reactors. The production process development also aims to obtain a larger production capacity than previous studies. This study uses varying weights of EFB produced into bio-coal, namely 250, 500 and 1000 grams, with a torefaction process temperature of 200°C for 30 minutes. As a result, the peat water flow rate decreased K, Cl and K2O content to the lowest content reduction value, which amounted to 8.31%, 0.42% and 3.96%, respectively. The heating value of bio-coal produced in a fixed bed reactor is 26,166 kJ/kg, while in a continuous tubular reactor, it is 21,720 kJ/kg. Based on these results, the fixed bed reactor shows a higher heating value than the continuous tubular reactor. The heating value obtained from these two types of reactors is comparable to sub-bituminous coal, which is usually used in steam power plants.
Drug forecasting and supply model design using Artificial Neural Network (ANN) and Continuous Review (r, q) to minimize total supply cost Izzati, Inaya; Sriwana, Iphov Kumala; Martini, Sri
SINERGI Vol 28, No 2 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2024.2.002

Abstract

The Mentawai Islands Regency Regional General Hospital faces a significant challenge with an 83% overstock of Medical Consumables, leading to increased inventory costs and potential damage and expiration of items. This exceeds the 1% pharmaceutical drug storage standards the Ministry of Health set. This study aims to optimize demand forecasting and minimize total inventory costs through a two-stage process. Firstly, demand forecasting is conducted using Artificial Neural Network (ANN), predicting a future demand of 10,036 units of Medical Consumables. Subsequently, the optimal order quantity and reorder points are calculated using the continuous review (r, Q) approach. The results reveal the optimal order quantities and reorder points for four types of Medical Consumables. This research introduces a novel approach by employing ANN for demand forecasting, then calculating optimal order quantities and reorder points using continuous review (r, Q). The cost components considered in the inventory cost calculation include purchasing cost, holding cost, shortage cost, order cost, outdating cost, and inspection cost. The designed forecasting models aim to enhance inventory management efficiency, optimize cost control, and improve patient services. The limitation of this research is that it only used five types of consumable medical materials to carry out this research due to limited data access. It is hoped that future research can use other types of drugs as well as a periodic review and forecasting approach using GA.
Battery Energy Storage System (BESS) as a voltage control at substation based on the defense scheme mechanism Arifin, Zainal; Firmanto, Aditya; Dwirawan, Sirilus; Alwani, Dede Rilwan
SINERGI Vol 28, No 2 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2024.2.001

Abstract

Battery Energy Storage Systems (BESS) can improve power quality in a grid with various integrated energy resources. The BESS can adjust the supply and demand to maintain a more stable, reliable, and resilient power system. Connected to the grid, BESS can respond quickly as a voltage regulator on the grid in the event of a voltage drop during peak load or when a disturbance occurs. Thus, the equipment has designed a voltage regulation scheme to prevent voltage drops and poor power quality caused by some rapid voltage fluctuations. This study investigates the role of BESS as a voltage control combined with a defense scheme mechanism at a high-voltage network in Jakarta. ETAP modeling software has investigated several voltage regulation systems with BESS at the substation indications. The results showed that the BESS at Substations can improve the voltage quality on the grid through voltage regulation. 
Students’ emotion classification system through an ensemble approach Muhajir, Muhajir; Muchtar, Kahlil; Oktiana, Maulisa; Bintang, Akhyar
SINERGI Vol 28, No 2 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2024.2.020

Abstract

Emotion is a psychological and physiological response to an event or stimulus. Understanding students' emotions helps teachers and educators interact more effectively with students and create a better learning environment. The importance of understanding students' emotions in the learning process has led to exploring the use of facial emotion classification technology. In this research, an ensemble approach consisting of ResNet, MobileNet, and Inception is applied to identify emotional expressions on the faces of school students using a dataset that includes emotions such as happiness, sadness, anger, surprise, and boredom, acquired from students of Darul Imarah State Junior High School, Great Aceh District, Indonesia. Our dataset is available publicly, and so-called USK-FEMO. The performance evaluation results show that each model and approach has significant capabilities in classifying facial emotions. The ResNet model shows the best performance with the highest accuracy, precision, recall, and F1-score, which is 86%. MobileNet and Inception also demonstrate good performance, indicating potential in handling complex expression variations. The most interesting finding is that the ensemble approach achieves the highest accuracy, precision, recall, and F1-score of 90%. By combining predictions from the three models, the ensemble approach can consistently and accurately address emotion variations. Implementing emotion classification models, individually and in an ensemble format, can improve teacher-student interactions and optimize learning strategies that are responsive to students' emotional needs. 
Usability Evaluation for Mobile Health Application: Systematic Literature Review Septiani, Winnie; Rahmawati, Novia; Safitri, Dian Mardi; Luis, Martino
SINERGI Vol 28, No 2 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2024.2.009

Abstract

Health applications have unique characteristics compared to other applications. This application is needed to support the health of users/families with various facilities provided according to their functions and objectives. Usability measurement is carried out to evaluate the successful use of the application using various usability criteria. This study aimed to identify, analyze, and synthesize the usability evaluation of a mobile health application. The review was carried out on 65 selected papers from 799 usability papers from the Web of Science and Scopus in the 2013 to 2023 time period. The Systematic Literature Review approach used is the Preferred Reporting Item for Systematic Reviews and Meta-Analysis (PRISMA). Based on the review results, it was identified that usability measurement on mobile health applications aims to validate system design, compare usability methods, improve application performance, and evaluate usability. Meanwhile, mHealth apps mostly function for treatment and self-care/self-management. Most of the reviewed papers used the general public as respondents. The respondents or participants in these studies are diverse and can be categorized into five groups: patients, healthcare professionals, older adults, experts, and the general public. Most of the research aims to evaluate usability with the most widely used method, the System Usability Scale, which is equipped with other supporting methods.
Analysis of empirical method for predicting maneuverability of ultra-large container ship using Maneuvering Modelling Group (MMG) model Zeinurrohman, Rangga; Trimulyono, Andi; Wicaksono, Ardhana; Hadi, Eko Sasmito; Samuel, Samuel; Hakim, Muhammad Luqman; Purwanto, Dedi Budi
SINERGI Vol 28, No 2 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2024.2.016

Abstract

International Maritime Organization (IMO) provided manoeuvrability standards for all ships above 100 m to ensure the ship's safety and surroundings. In the preliminary design stage, one way to ensure a ship's manoeuvrability under IMO standards is to use empirical methods that are cheaper and less time-consuming than model tests. Empirical methods used analysis regression to develop their formula from the model test result database, and their formula depends on ship hull parameters and dimension ratios such as , , , and . However, the database of the existing empirical formulas is limited to small-medium merchant ships and fishing vessels, as consequences for larger ships are inaccurate and have a significant error in predicting ship manoeuvres. This study modified the existing empirical formulas by adding specified ship data into the existing database and analyzing the accuracy of predicting ship manoeuvres using the Maneuvering Modelling Group (MMG) model. We verify by adding the selected ship data into the existing database, which shows improvement in predicting ship manoeuvres. The modified formulas show improvement by only giving 5% RMSE of tactical diameter and 3% RMSE of ship advance in turning manoeuvre, and this is a 78% overall improvement in predicting the turning motion of ultra-large container ships compared to previous formulas. The quantitative and qualitative produce better estimation result that indicates the right track to derive the empirical formulas for Ultra-Large Container ships.
Problem solving path planning and path tracking in a 3 DOF hexapod robot using the RRT* algorithm with path optimization and Pose-to-Pose Suwoyo, Heru; Burhanudin, Achmad; Tian, Yingzhong; Andika, Julpri
SINERGI Vol 28, No 2 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2024.2.007

Abstract

Path planning is one of the most fundamental problems that must be solved before a robot can navigate and explore autonomously. Path planning needs to be integrated with path tracking to be applied to autonomous robots. This makes path tracking also important for autonomous robot navigation which cannot be separated from path planning. There are two path planning methods, the first is search-based method, the second is sampling-based method. Both have their own advantages, but the popular and commonly used sampling-based algorithm due to its fast convergence is preferred in path planning.  The RRT* algorithm was developed. This improvement initiated a major civilization in sampling-based algorithms, namely parent node selection and rewiring in RRT. Although there has been an improvement in optimality, RRT* still doesn't provide the distance optimality value as expected, due to its character that is still adopted from RRT.  The resulting path is still suboptimal and not smooth (jagged). On the other side, Path tracking has several methods, however, these path tracking methods are difficult to apply to autonomous robots and need to be adapted to the robot used. Based on the description above, there are still problems with path planning, namely paths that are still less than optimal and convergence that is still slow.  This research will add a way to shorten the distance in the RRT* algorithm with the triangular inequality method.  Meanwhile, for path tracking, we will apply the pose-to-pose method, which follows the waypoint that has been made by path planning.

Page 1 of 3 | Total Record : 22

 1   2   3 

Filter by Year

2024 2024


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