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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 16 Documents
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Search results for , issue "Vol 27, No 2 (2023)" : 16 Documents clear
Sentiment Analysis From Twitter About Covid-19 Vaccination in Indonesia Using Naive Bayes and Xgboost Classifier Algorithm Alvin Irwanto; Leonard Goeirmanto
SINERGI Vol 27, No 2 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.2.001

Abstract

The pandemic that hit the world has greatly impacted our life. But after some time, it seems that it will be going to end because the vaccine has already been made. In response to this, some people expressed their opinions about this vaccination on social media, for example, in the form of tweets on Twitter. The authors use those opinions or tweets as sentiment analysis material to determine the assessment of this vaccination. The tweet data in this study was obtained through data crawling using the Twitter API with the Python programming language. The variables used in this case are public tweets and their sentiments. This sentiment analysis process uses the Classification method with the Naive Bayes Classifier and will be compared with the XGBoost Classifier algorithm. The results of this study indicate that people are more likely to respond positively to this vaccination. In this case, the Naive Bayes Classifier got better performance with 0.95 from ROC - AUC Score and 134 ms in runtime compared to the XGBoost Classifier algorithm with 0.882 in ROC - AUC Score and 1 minute and 59 seconds in runtime.
Effect of one-year corrosion on steel bridge materials in the maintenance stage with the Charpy impact test method Fauzri Fahimuddin; Mudiono Kasmuri; Rikki Sofyan; Syarif Junaidi; Latha MS
SINERGI Vol 27, No 2 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.2.002

Abstract

Corrosion of steel bridges is a major problem because it has the potential to reduce the performance of the structure over its lifetime. One factor that should not be reduced is fracture toughness, so this should be a very important concern in the maintenance program. Existing guidelines do not specify when corrosion conditions are hazardous and when corrosion conditions are not hazardous to structural performance. This study aims to explain how long corrosion does not cause danger, and when corrosion becomes dangerous. The Charpy Impact Test was used in this study to examine the effect of corrosion with a corrosion duration of weekly up to one year on fracture toughness. The series of tests in this research program used SM-490-type specimens which are steel plates commonly used for bridge structures. Specimens with variations in corrosion duration which were the result of immersion in sulfuric acid solution to simulate corrosion growth were then subjected to crack toughness testing. The toughness of each specimen was tested with a corrosion period starting from 1 week and so on up to 1 year to determine the level of fracture toughness. The results obtained from all tests showed that there was no decrease in the toughness of the corroded specimens for up to 1 year. The data presented in this study is very helpful for the designers and maintainers to plan corrosion treatment programs with clearer and more accurate considerations in assessing the structural integrity of steel bridges affected by corrosion.
Modelling effects of water stress on the productivity of irrigated wheat (Triticum Aestivum L.) in a semiarid condition of Northeastern Nigeria Muhammad Mansur Haruna; Ali Umar Bashir; Habibu Ismail; Mohammed Sani
SINERGI Vol 27, No 2 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.2.010

Abstract

Lake Chad region is currently experiencing trending issues. Climate change is among the major influencers of these issues that require inevitable consideration for a sustainable ecosystem. Various crop models have been developed and employed in various environmental conditions and management practices, which are cheaper and easier than field experiments. Therefore, crop models could be used to simulate various water management strategies and suggest suitable options. In this work, the FAO AquaCrop model has been evaluated to simulate deficit irrigation (DI) scenarios for wheat crops using data generated from a field experiment. The model simulated grain yield (GY), biomass yield (BMY), biomass production (BMP) and canopy cover (CC) adequately during its calibration and validation. However, its performance in simulating water productivity (WP) and actual crop evapotranspiration (ETa) was low with average r2, NRMSE, model efficiency (EF) and Willmot Index of agreement (d) of 0.58, 11.0 %, -1.40 and 0.69 respectively. The study of DI scenarios using the model revealed that the application of DI throughout the growth stages of the crop could significantly affect GY and WP. The highest GY and WP of 5.3 t/ha and 1.50 kg/m3 were respectively obtained at the application of full irrigation (T100). Increasing DI beyond 20 % depressed both GY and WP significantly. However, increasing the irrigation interval from seven to ten days did not affect GY, thereby improving WP from 1.28 kg/m3 to 1.38 kg/m3. Therefore, applying an 80 % irrigation requirement throughout the wheat growing season at 10-day intervals could save 25 % of irrigation water, a valuable strategy to improve irrigation water use without significant yield reduction. Furthermore, irrigation-related scientists and managers can use the validated model to decide the current and future irrigation water management for similar wheat varieties in similar environmental conditions.
Induced roll magnetic separator applied for high grade ilmenite separation from mining tailing Wiwik Dahani; Rita Sundari; Subandrio Somali; Irfan Marwanza; Andriyani Andriyani; Djoko Hartanto; Khuzaimah Arifin; Ratna Ediati
SINERGI Vol 27, No 2 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.2.015

Abstract

This article aimed to separate ilmenite (FeTiO3) mineral from tin tailing applying a single splitter IRMS (Induced Roll Magnetic Separator). Ilmenite mineral is the substantial main source for TiO2. This work used air table middling for feeding. The mineral components of middling feeding from air table using grain counting analysis were found as follows: cassiterite (48.61%), ilmenite (21.36%), monazite (18.56%), pyrite (4.60%), zircon (5.85%), quartz (0.71%), anatase (0.27%), and tourmaline (0.02%), It was found that electrical current and opening of single splitter affected the degree of separation addressing to ilmenite recovery and ilmenite grade. The finding showed that current of 15 Ampere and single splitter with opening 4.25 cm yielded ilmenite recovery more than 74%. The high grade ilmenite (90.46 %) and recovery of 29.38% was obtained using 5 Ampere  with single splitter opening of 1.0 cm. Up to date, the study on ilmenite separation from tailing only focused on the effect of current, however, the effect of single splitter magnetic separator  to enhance ilmenite recovery from other paramagnetic minerals such as monazite, siderite, xenotime and tourmaline has not yet been reported. 
Identification of operational risk of embedded Subscriber Identity Module (SIM) technology based on ISO 31000: Systematic Literature Review Dian Elok Pertiwi; Lien Herliani Kusumah
SINERGI Vol 27, No 2 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.2.007

Abstract

In the current digital era, telecommunications industry technology is growing rapidly, impacting the demands for innovation in the telecommunications operator business. One of them is the change in the size of the Subscriber Identity Module (SIM) card model, which is getting smaller, and the use of embedded SIM (eSIM) technology on smartphones. This study aims to identify operational risk factors from the change in SIM card technology to eSIM. The research method used is the Systematic Literature Review (SLR) method. This study documents and reviews scientific journal papers from scientific databases published from 2015 to 2022 on risk management in the information technology field, following this research's objectives. The results obtained from this study showed that there were 43 journals studied, of which four had the theme of technology-embedded subscriber identity module (eSIM), and 13 discussed risk operations technology
Model predictive control with exogenous auto-regressive model to improve performance in the CO2 removal Abdul Wahid; Nisa Methilda Andriana Rodiman; Alifia Rahma; Arshad Ahmad; Andri Kapuji Kaharian
SINERGI Vol 27, No 2 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.2.011

Abstract

Model predictive control (MPC) is used in the CO2 removal process in the Subang field to improve its control performance. MPC is used to maintain the CO2 concentration at the sweet gas output by controlling the feed gas pressure (PIC-1101), makeup water flow rate (FIC-1102), and amine flow rate (FIC-1103). The empirical model applied to MPC to represent the process model is the auto-regressive exogenous (ARX) model. The ARX model is compared with the first order plus dead time (FOPDT) model based on the root mean square error (RMSE) between the model and the actual process, then MPC parameters are tuned which include sampling time (T), prediction horizon (P) and control horizon (M) to control for the three variables. Improved control performance is measured based on the integral square error (ISE). The results show that the ARX model is the best model for the CO2 removal process with an RMSE value of 35%-91% smaller than the FOPDT model. The optimal control parameters Prediction Horizon (P), Control Horizon (M) and Sampling Time (T) in the CO2 removal process are 75, 25 and 1 on PIC-1101, 25, 10 and 1 on FIC-1102, and 30, 25 and 1 on FIC-1103. The MPC-ARX (MPC using ARX model) can improve the control performance of 33% in the servo control and 6-56% on the regulatory control. However, not all of them showed an increase in control performance improvement from previous studies even though they had used the best model (ARX). This is due to the MPC parameter setting that is not yet appropriate, so it needs to be retuning.
The assessment of drainage performance in the residential area using SWMM Yuliastuti Juliastuti; Timotius Kurniawan Wihartono; Oki Setyandito; Yureana Wijayanti; Lisma Safitri; Ika Sari Damayanti Sebayang
SINERGI Vol 27, No 2 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.2.016

Abstract

Flood is a general issue that can lead to the life and safety of residents. One of the problems is the lack of capacity in the drainage system in a residential area. This paper will analyze the drainage system based on the capacity in one of the residential clusters. The method for the drainage system performance in hydrology analysis was carried out with Log Person, and the return period for rainfall duration is ten years (R10) for hydraulic analysis using drainage system modeling with EPA – SWMM 5.1. The result based on hydrological is the precipitation for flood forecasting is 159.79 mm. It is found that the drainage capacity is filled in downstream of the main drain with a maximum discharge of 2.726 m3/s and secondary drains with a maximum discharge of 0.624 m3/s. Improvements were made to resolve the insufficiency of the existing channels by running two different scenarios: (1) Re-design the dimensions of the main and secondary channels, (2) Implement a detention pond, as well as re-design the dimensions of the secondary channels. Both scenarios could overcome the flood problem. Scenario 2 shows a higher reduction in the flow discharge at the downstream channel compared to scenario 1.  
Multilabel image analysis on Polyethylene Terephthalate bottle images using PETNet Convolution Architecture Khoirul Aziz; Inggis Kurnia Trisiawan; Kadek Dwi Suyasmini; Zendi Iklima; Mirna Yunita
SINERGI Vol 27, No 2 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.2.003

Abstract

Packaging is one of the important aspects of the product. Good packaging can increase the competitiveness of a product. Therefore, to maintain the quality of the packaging of a product, it is necessary to have a visual inspection. Furthermore, an automatic visual inspection can reduce the occurrence of human errors in the manual inspection process. This research will use the convolution network to detect and classify PET (Polyethylene Terephthalate) bottles. The Convolutional Neural Network (CNN) method is one approach that can be used to detect and classify PET bottle packaging. This research was conducted by comparing seven network architecture models, namely VGG-16, Inception V3, MobileNet V2, Xception, Inception ResNet V2, Depthwise Separable Convolution (DSC), and PETNet, which is the architectural model proposed in this study. The results of this study indicate that the PETNet model gives the best results compared to other models, with a test score of 96.04%, by detecting and classifying 461 of 480 images with an average test time of 0.0016 seconds.
The influence of heat rate and austenitization temperature on microstructure and hardness of Hadfield steel Haris Wahyudi; Swandya Eka Pratiwi; Adolf Asih Supriyanto; Daisman Purnomo Bayyu Aji
SINERGI Vol 27, No 2 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.2.012

Abstract

The As-Cast condition of Hadfield alloy usually contains (Fe, Mn)3C carbides around the austenitic grains, which promote brittleness, making the steel impractical in industry. Heat treatment is normally applied to reduce carbide content, lower carbides, and improve toughness. However, a complete austenitic structure is not attainable during solution treatment. The dissolution temperature and dissolution time are critical to obtaining complete carbide content. Furthermore, heating must be done slowly, and the quenching speed must be fast enough. This study examines the effect of heat rate and austenitization temperatures in the solution treatment on the microstructure and hardness of Hadfield steel. The heat rate of 3, 6 and 10 oC/min is selected to determine whether there is a change in the microstructure of Hadfield steel. The four austenitization temperatures of 1000, 1100, 1150 and 1200 oC are used to ascertain carbide dissolution into the austenite matrix. Grain boundary, hardness, and phase transformation will confirm the microstructural change and hardness properties. The optical microscope shows carbide content is reduced as the austenitization temperature increases. The consequence of carbide dissolution affects the hardness. Its hardness decreases as temperature increase due to the loss of carbide. The as-Cast specimen has the highest hardness of 227.8 HV30, and the lowest hardness is 176.7 HV30 belongs to a specimen that is heated up to 1200 °C and quenched into water. Grain size is measured by the line intercept method, which shows its increase as temperatures increase. The result of grain measurement is as follows: As-Cast 224.6 mm, T 1000 °C 323.3 mm, T1100 °C 409.2 mm, T1150 °C 1014.4 mm, T1200 °C 881.6 mm. SEM-EDS confirms that the main phase is austenite, and a small amount of carbide is detected in the austenite matrix. 
Utilizing waste heat gasoline engine in the design and fabrication of a fin and tube evaporator for the Organic Rankine Cycle (ORC) Awaludin Martin; Rudi Hartono; Reza Asrian
SINERGI Vol 27, No 2 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.2.004

Abstract

The excessive consumption of fossil fuels is causing environmental problems, which can be addressed by utilizing renewable energy sources such as hydro energy, biomass, solar heat, geothermal, and waste heat. In particular, the exhaust gas from gasoline engines presents an opportunity for energy recovery, as only 25% of the energy is utilized while the remaining 75% is wasted. A fin and tube type evaporator was designed, manufactured, and tested to utilize this exhaust gas in an Organic Rankine Cycle (ORC) system. The evaporator was designed with an outer tube diameter of 9.525 mm and a total tube length of 41.4 m, featuring 90 tubes and 135 fins with a total area of 14,325 m2. It achieved an average effectiveness of 94.33%. The results showed that the waste heat from the exhaust gas of a gasoline engine could be used as a source of energy in an ORC system with an efficiency of 2.13%. It results in 7.02 kJ/s of energy absorbed by the evaporator and a net power generated of 0.15 kJ/s. This research demonstrates the potential for utilizing waste heat from gasoline engines as an energy source to generate electricity.

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