Sinergi
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.
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<![CDATA[FEASIBILITY STUDY OF A RAILWAY CONSTRUCTION PROJECT AS INTERMODAL TRANSPORTATION IN TANJUNG PERAK PORT ]]>
<![CDATA[Kevin Arga]]>;
<![CDATA[Budi Susetyo]]>;
<![CDATA[Syafwandi Syafwandi]]>
<![CDATA[ SINERGI Vol 25, No 1 (2021) ]]>
Publisher : <![CDATA[Universitas Mercu Buana ]]>
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DOI: 10.22441/sinergi.2021.1.008
<![CDATA[The growth of container flows that is not supported by infrastructure needs has caused goods congestion at Tanjung Perak Port. The situation has an impact on the flow of goods and makes container mobilization stop flowing. Railway infrastructure construction is expected to overcome the problem of goods congestion, especially because this project will be integrated with other transportation at the Port in an intermodal transportation system. The Delphi method is used as an approach to get the dominant aspect to be analyzed in a feasibility study of a railway construction project at the Port of Tanjung Perak. Delphi method results show that the financial aspect and market aspect are the dominant parameters to be analyzed in the feasibility study of a railway construction project. The results of the market feasibility analysis showed that 87.67% of stakeholders agreed with the railway development project plan, with a target market of 19.99% of the number of containers and absorption of around 84% of the target market. The results of the financial feasibility analysis are obtained, the Net Present Value (NPV) is 1,184,370> 0 (profitable project), the Benefit-Cost Ratio (BCR) is 1.39 ≥ 1 (the project is feasible), and the value of the Internal Rate of Return (IRR) is 13%> MARR, (investment is feasible). From the results of the financial feasibility analysis, the railway construction project is categorized as possible. Meanwhile, the break-even point for this project is in the 12th year with the results of a profit-loss analysis showing that in the fourth year, the railway operational activities have shown a positive trend/profit.]]>
<![CDATA[EFFECT OF HOT DIPPING ALUMINIZING ON THE TOUGHNESS OF LOW CARBON STEEL ]]>
<![CDATA[Dody Prayitno]]>;
<![CDATA[Ammar Abyan Abdunnaafi]]>
<![CDATA[ SINERGI Vol 25, No 1 (2021) ]]>
Publisher : <![CDATA[Universitas Mercu Buana ]]>
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DOI: 10.22441/sinergi.2021.1.010
<![CDATA[Steel that has been aluminized said as hot dipping aluminizing has better protection against corrosion and can protect against temperatures as high as 800°C. In hot dipping aluminizing, Steel is immersed into a molten aluminium for certain dipping time. The research aims to know the effect of preheating and dipping time on the toughness of low carbon steel. The method research was started by cutting the low carbon steel plate, according to ASTM E23 (Charpy test sample) into 16 pieces samples. Then the samples were grouped into four groups. Group-1 was initial samples. The Group-2 was directly immersed into molten aluminum 700 0C, for dipping time 5 minutes. The Group-3 was preheated at 700 oC for 30 minutes and then to be aluminized (700 oC) for dipping time 5 minutes. The Group-4 was preheated at 700 oC for 30 minutes and then to be aluminized (700 oC) for dipping time 10 minutes. Finally, all groups were tested by the Charpy test at room temperature. The results show that the aluminizing increases the toughness of low carbon steel from 228.125 KJ/m2 to 312.5 KJ/m2. The preheating process before aluminizing increases sharply the toughness of low carbon steel from 228.125 KJ/m2 to 512.5 KJ/m2. The increasing dipping time from 5-minute to 10-minute increase gradually the toughness from 512.5 KJ/m2 to 556.25 KJ/m2.]]>
<![CDATA[TIRE WASTE AS A POTENTIAL MATERIAL FOR CARBON ELECTRODE FABRICATION: A REVIEW ]]>
<![CDATA[Ahmad Ariri]]>;
<![CDATA[Sagir Alva]]>;
<![CDATA[Siti Aishah Hasbullah]]>
<![CDATA[ SINERGI Vol 25, No 1 (2021) ]]>
Publisher : <![CDATA[Universitas Mercu Buana ]]>
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DOI: 10.22441/sinergi.2021.1.001
<![CDATA[Nowadays, tire waste is a big issue since the rapid growth of vehicle population worldwide. The disposal of tire waste should be done properly due to the environmental impact caused by stockpile the tire waste in landfill. Many kinds of research had been conducted to dispose of tire waste efficiently for getting valuable material from tire waste by using pyrolysis technology; one of them is carbon. In this review paper, production and application of carbon from tire waste presented. In several studies, carbon derived from tire waste was used as an adsorbent, electrode in energy storage application, like batteries and fuel cell.]]>
<![CDATA[MELASTOMA MALABATHRICUM L. EXTRACTS-BASED INDICATOR FOR MONITORING SHRIMP FRESHNESS INTEGRATED WITH CLASSIFICATION TECHNOLOGY USING NEAREST NEIGHBOURS ALGORITHM ]]>
<![CDATA[Aliefia Noor]]>;
<![CDATA[Evi J.]]>;
<![CDATA[Aisyah D. A. T. Safitri]]>;
<![CDATA[Mustari Mustari]]>;
<![CDATA[Yuant Tiandho]]>
<![CDATA[ SINERGI Vol 25, No 1 (2021) ]]>
Publisher : <![CDATA[Universitas Mercu Buana ]]>
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DOI: 10.22441/sinergi.2021.1.009
<![CDATA[As a maritime country, shrimp commodity production in Indonesia is very high and continues to increase. However, because shrimp is a perishable food, we need a detection device. This is because conventional methods that are widely used by the community in detecting freshness of shrimp are only based on the smell. Of course, this is a problem when shrimp are packed in closed containers. In this paper, a method for detecting shrimp is proposed using the Melastoma malabathricum L. - based label indicator. The high content of flavonoids in the extracts allows the changing the colour of the label from red to grey due to the interaction between the label with the OH- group that arises from the shrimp spoilage process. The colour that appears on the label indicator will correlate with the level of shrimp freshness. By increasing detection effectiveness, the classification is performed using the nearest-neighbours algorithm, which is equipped with an image processing mechanism in the form of colour quantization. There are four classifications used to express the quality of shrimp, namely "acceptable," "just acceptable," "unacceptable," and "more unacceptable." The accuracy of applying this method is 71.9%, with the majority of detection errors occurring in the "acceptable" class. Based on these results, it can be stated that the label indicators prepared in this study are very promising to be developed into intelligent packaging components.]]>
<![CDATA[DESIGN MODELING OF SAVONIUS-DARRIEUS TURBINE FOR SEA CURRENT ELECTRIC POWER PLANT ]]>
<![CDATA[Boris Metheny]]>;
<![CDATA[Rosyida Permatasari]]>;
<![CDATA[Muhammad Sjahrul Annas]]>
<![CDATA[ SINERGI Vol 25, No 1 (2021) ]]>
Publisher : <![CDATA[Universitas Mercu Buana ]]>
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DOI: 10.22441/sinergi.2021.1.004
<![CDATA[Turbines convert the kinetic energy of ocean currents into electrical energy produced by the sea current electric power plant. This study aims to design a power generator turbine modeling that is carried out using the Computational Fluid Dynamic (CFD) approach by comparing the geometric performance based on the angle of attack and the Tip Speed Ratio (TSR) value of the Savonius-Darrieus Turbine. Having done several trials and errors during collecting the data, the value of the TSR 1.427; 2.853; 4.28; 5; and 5.7 is proposed. Here, the NACA 0018 series has been adopted on the current design of Savonius-Darrieus Turbine. The turbine has three blades, length of the span 357 mm, the diameter of turbine 428 mm, and length of the hydrofoil chord 40 mm. Effect of various angle of attacks from 0°up to 10° has been taken into account in the computational to obtain the coefficient power for each variation. The results revealed that the turbine with an angle of attack of 5°and TSR value of 5.0 has higher power coefficient value by 0.469 as compared with its angle of attack of 10°. It should be noted here that the increase of the angle of attack up to 10° resulted in a significant reduction of the power coefficient value of 0.206 as the value of TSR about 4.28. The addition of the Savonius Rotor results in increasing efficiency of the turbine for sea current applications.]]>
<![CDATA[QUALITY ASSURANCE OF BOTTLED DRINKING WATER USING THE HAZARD ANALYSIS CRITICAL CONTROL POINT SYSTEM APPROACH ]]>
<![CDATA[Wilson Kosasih]]>;
<![CDATA[Lithrone Laricha Salomon]]>;
<![CDATA[Andrian Andrian]]>;
<![CDATA[Siti Rohana Nasution]]>;
<![CDATA[Silvi Ariyanti]]>
<![CDATA[ SINERGI Vol 25, No 1 (2021) ]]>
Publisher : <![CDATA[Universitas Mercu Buana ]]>
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DOI: 10.22441/sinergi.2021.1.002
<![CDATA[This paper discusses on implementing the design of a quality assurance system using the Hazard Analysis Critical Control Point HACCP approach. The HACCP is often considered by people who are not familiar as a problematic, complicated system that has to be left to experts. This system focuses on preventive measures by controlling the hazards of the drinking water treatment process to prevent the occurrence of diseases due to poisoned water and maintain product quality. This research was conducted at a bottled drinking water company. This company needs to commit to producing products that are hygienic and safe for consumption. In this study, laboratory testing of the finished goods was intended to determine the conformance quality of the product. The sample test result found the coliform bacteria in the bottled drinking water product. At last, this study developed critical control points in the daily operations by applying the whole HACCP principles based on the latest applicable standards.]]>
<![CDATA[THE CHARACTERISTICS OPERATIONAL COST OF FREIGHT TRANSPORT IN SOUTH SULAWESI PROVINCE - INDONESIA ]]>
<![CDATA[Hakzah Hakzah]]>;
<![CDATA[Muhammad Isran Ramli]]>;
<![CDATA[Andi Irmayani Pawelloi]]>
<![CDATA[ SINERGI Vol 25, No 1 (2021) ]]>
Publisher : <![CDATA[Universitas Mercu Buana ]]>
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DOI: 10.22441/sinergi.2021.1.011
<![CDATA[Infrastructure development of the freight transport system has a vital position in accelerating Indonesian economic growth. This study aims to analyze one of the dominant characteristics of freight transportation, namely freight transportation costs in South Sulawesi Province. A questionnaire-based interview survey of operators was conducted to determine operator characteristics, vehicle characteristics, trip characteristics, and commodity characteristics. They are analyzing data using a descriptive statistical approach, building a cost and distance relationship model using a regression model approach while analyzing the priority of freight transport selection using an Analytical Hierarchy Process (AHP). An AHP is a decision-making model with multiple criteria. The analysis shows that the high costs are the component costs of the operator’s salary, fuel costs, and vehicle maintenance costs. Operating cost modelling provides a good level of models, both in terms of modes and commodities transported. In contrast, the travel time model based on modes and types of commodities shows inefficient. Based on the results, the pickup mode is optimal in cost and travel time with a weight of 39.8% and 50.3%. Trucks 3-4-5 Axles are the optimal mode of transportation when viewed in terms of distance (58.8%) and transportation volume (65.5%). In contrast, the two Axles Truck has characteristics between Pickups and 3-4-5 Axles Trucks. This result is better developed for a more comprehensive model of the cost of freight transport in South Sulawesi Province, Indonesia. ]]>
<![CDATA[THE IMPLEMENTATION OF ARTIFICIAL NEURAL NETWORKS IN DESIGNING INTELLIGENT DIAGNOSIS SYSTEMS FOR CENTRIFUGAL MACHINES USING VIBRATION SIGNAL ]]>
<![CDATA[Dedik Romahadi]]>;
<![CDATA[Fajar Anggara]]>;
<![CDATA[Andi Firdaus Sudarma]]>;
<![CDATA[Hui Xiong]]>
<![CDATA[ SINERGI Vol 25, No 1 (2021) ]]>
Publisher : <![CDATA[Universitas Mercu Buana ]]>
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DOI: 10.22441/sinergi.2021.1.012
<![CDATA[It is important to maintain every machine affecting the process of making sugar to ensure excellent product quality with minimal losses and to accelerate productivity and profitability targets. The centrifuges are widely used in industry today with some being very difficult and critical for surgery, and the collapse of the engine has the ability to cause expensive damage. One of these is the centrifugal machines, and they are expected to be efficient to produce high-quality sugar. Meanwhile, an efficient diagnostic tool to predict the correct time for centrifugal repair is vibration signal analysis namely by attaching the accelerometer sensor to the location of the centrifugal bearing to produce vibration data that is ready to be analyzed. Still, the process requires sufficient insight and experience. The manual method usually used is complicated and requires a lot of time to obtain results of a centrifugal diagnosis. Therefore, this study was conducted to design an intelligent system to diagnose centrifugal vibrations using Artificial Neural Networks (ANN). The situation is involved in applying and training the concept of vibration analysis from spectrum data to ANN to produce diagnostic results according to the spectrum diagnosis reference. The results obtained were quite good with the largest cross-entropy value of 10.67 having 0% error value with the largest Mean Square Error value being 0.0023 while the smallest regression was 0.993. The test conducted on nine new spectrums produced eight true predictions and one false. The system can provide fairly accurate results in a short time. Classification quality improvement can be made by adding training data.]]>
<![CDATA[DESIGN PROCESS OF DME STORAGE SYSTEM AS ASSEMBLY PARTS OR MAINTENANCE SPARE PARTS INVENTORY IN OFFSHORE OIL DRILLING PIPING SYSTEM ]]>
<![CDATA[Sally Cahyati]]>;
<![CDATA[Daniel Rizky Mahendra]]>
<![CDATA[ SINERGI Vol 25, No 1 (2021) ]]>
Publisher : <![CDATA[Universitas Mercu Buana ]]>
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DOI: 10.22441/sinergi.2021.1.003
<![CDATA[Discharge Manifold Equipment (DME) is an output pipe from a pump that bears an essential role in a piping system in offshore oil drilling, so it is a must to assure good bears condition whenever used. It is not an easy thing because DME is a significant and heavy component. Also, unfavourable conditions of offshore climate can accelerate its corrosion. Storage with the modular rack uses an offshore container certified DNV 2.7-1 / EN 12079 will be designed to fulfil those needs. The storage has an important role as an element in inventory, both the storage system for assembly parts or maintenance spare parts. This storage will be design using 4 (four) phases from VDI 2221 methods, namely; task clarification, conceptual design, embodiment design, and detailed design. Hydraulic power will be added to the system to support the piston movement so that the storage rack can be moved automatically by the hydraulic system. This storage has given the best solution for a systematic storing DME in the piping system of offshore oil drilling.]]>
<![CDATA[K-MEANS CLUSTERING FOR EGG EMBRYO'S DETECTION BASED-ON STATISTICAL FEATURE EXTRACTION APPROACH OF CANDLING EGGS IMAGE ]]>
<![CDATA[Shoffan Saifullah]]>
<![CDATA[ SINERGI Vol 25, No 1 (2021) ]]>
Publisher : <![CDATA[Universitas Mercu Buana ]]>
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DOI: 10.22441/sinergi.2021.1.006
<![CDATA[This research discusses the detection of embryonic eggs using the k-means clustering method based on statistical feature extraction. The processes that occur in detection are image acquisition, image enhancement, feature extraction, and identification/detection. The data used consisted of 200 egg image data, consisting of 100 test data and 100 new test data. The acquisition process uses a smartphone camera by capturing candled egg objects. The results of image acquisition become a reference in the process of image enhancement and feature extraction using Statistical Feature Extraction. The statistical feature extraction applied is the Gray Level Co-occurrence Matrix (GLCM) method, which consists of 6 features, namely Energy, Contrast, Entropy, Variance, Correlation, and Homogeneity. The results of feature extraction (6 features) are grouped by the K-means Clustering method. The clustering process uses Euclidean distance calculations to determine the proximity of features. The results of grouping and testing give the best average results with an accuracy of ≈ 74% from several test samples.]]>
