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L Edahwati
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Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Transportation

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Analysis of Combustion Temperature on the Use of B100 and B20 Fuels that Operate in the Long Term W Saputro; J Sentanuhady; L Edahwati; A K Faizin
BIOMEJ Vol. 2 No. 1 (2022): BIOMEJ
Publisher : UPN 'Veteran" Jawa Timur

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Abstract

Indonesian people's reliance on diesel fuel is still quite strong, as seen by the rising yearly use of diesel. Because diesel is a fossil fuel that is not renewable, rising diesel usage is a concern that must be anticipated. One approach to deal with this is to switch from fossil fuels to biofuels like biodiesel. Because Indonesia is the world's largest producer of palm oil, biodiesel from palm oil is an alternative. Although biodiesel may potentially be used directly in diesel engines, there are few researches on the impacts of utilizing it and the possibility for further development. As a result, the goal of this research is to look at the combustion temperature of B100 and B20 fuels in long-term testing. Two Kubota diesel engines with 376 cc cylinder volumes are used in this investigation. Each engine will be connected to a generator that will provide 4000 W of electricity to the halogen bulbs. The two engines will run on separate fuels, with the first using B20 and the second on B100 from palm oil. The engine has a continuous rotational speed of 2200 rpm and has been running for 300 hours without stopping. The combustion temperature of the cylinder head, cylinder block, and exhaust gas pipe is measured every multiple of 4 hours. With 1.7 percent, 1.2 percent, and 2.7 percent, respectively, the B100 engine delivers lower combustion temperatures in the cylinder head, cylinder block, and pipe exhaust gas.
Secondary Flow Phenomenon at Elbow Ducting of The Closed-Circuit Subsonic Wind Tunnel: An Experimental Study A K Faizin; Sutardi; L Edahwati; W D Lestari; N Adyono; R D Issafira; W Saputro; T P Sari
BIOMEJ Vol. 2 No. 1 (2022): BIOMEJ
Publisher : UPN 'Veteran" Jawa Timur

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The installation of elbow ducting in closed-loop wind tunnel installation will cause a pressure drop. Pressure drop was caused by flow separation and secondary flow phenomenon in the elbow ducting. The test section used in this experimental study was an octagonal elbow 90º with radius ratio (rm/Dh) = 0.6. Diameter hydraulic (Dh) elbow of 806 mm. In this study, the Reynolds number is measured based on the free flow velocity (U∞) inlet section, that is ReDh = 4.63x105. The experimental results showed the pressure drop is ΔCp = 1.46 for Re = 4.63x105. This difference in pressure value between the outer and inner (ΔCp) of the elbow ducting was caused by secondary flow. The secondary flow was observed through a horizontal velocity profile where at xi/Dh = 1.35, fluid flow was accelerated on the inner wall and decelerated on the outer wall of the ducting elbow. Then, at xi/Dh = 1.63 to xi/Dh = 2.01, there are gradual shifts of the velocity profile where the fluid flow is accelerated toward the outer wall.
Torque Load Analysis on Rear Axle Shaft Material AISI 4340 Normalized FA Nurmansyah; L Edahwati; RD Issafira; W Saputro; AK Faizin; TP Sari; WD Lestari; N Adyono
BIOMEJ Vol. 2 No. 2 (2022): BIOMEJ
Publisher : UPN 'Veteran" Jawa Timur

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The choice of rear axle shaft material on the car needs to be considered because this component affects the performance of the car. This component material is also very necessary, the selection of components used is AISI 4340 Steel Normalized, where this material contains Nickel, Chrom, and Molybden with the characteristics of the AISI 4340 Steel Normalized material is a steel material that has high hardness properties, can accept great pressure and force and not easy to deform. The method used is the Finite Element Method (FEM), this method uses a meshing size of 5 mm, to get more accurate results. Simulation results from rear axle shaft AISI 4340 Steel Normalized to determine the value of stress, strain, and safety factor from load variations of 1200 Nm, 1400 Nm, 1600 Nm, and 2000. The highest maximum stress value occurs at 2000 Nm torque load of 5.586 x 108 Nm. The highest maximum strain value occurs at a torque load of 2000 Nm of 5.034 x 103. The safest value of the safety factor is 2.1 at a torque load of 1200 Nm. The torque load value is directly proportional to the stress and strain values ​​obtained, because the greater the torque load value, the greater the stress and strain values ​​obtained.
Static Loading Analysis on Universal Joint Using Solidworks M Ikhsan; L Edahwati; RD Issafira; W Saputro; AK Faizin; TP Sari; WD Lestari; N Adyono
BIOMEJ Vol. 2 No. 2 (2022): BIOMEJ
Publisher : UPN 'Veteran" Jawa Timur

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This static loading analysis introduction training aims to analyze parts universal joints to the tensile test as an effort to accelerate the improvement of vocational teachers' abilities. In the introduction to analysis training this time using software CAD/CAM ie solidworks which is one software CAD/ CAM which is widely used in the manufacturing industry in terms of designing or analyzing a product design. The training method is carried out by first installing solidworks software to computer equipment, secondly making parts from universal joints, third assembling from parts that have been made, fourth doing drawing 2D from part and assembly that have been made, the five static loading analyzes of universal joint parts with tensile test. Election software this is based on its advantages such as easy to learn, widely used in industry, and can be used as a reference for studying software another. As a result of this training, it is hoped that the teachers of SMK Turen Malang will be able to make part3D models and 2D working drawings.
Artificial Neural Network Application for Sepsis Prediction: A Preliminary Study AK Faizin; W Saputro; RD Issafira; L Edahwati; WD Lestari; TP Sari; N Adyono
BIOMEJ Vol. 2 No. 2 (2022): BIOMEJ
Publisher : UPN 'Veteran" Jawa Timur

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Abstract

Sepsis is one of the leading causes of mortality in hospitalized patients. It is very difficult to find the symptoms of sepsis because of their similarity to the symptoms of other diseases. This paper aims to deliver an artificial neural network implementation in medical decisions support. This study tries to predict sepsis and healthy patient based on vital signs such as heart rate, systolic blood pressure, and diastolic blood pressure taken from the MIMIC-III clinical database. There were several extraction processes applied to vital sign signals such as using the statistical tools, discrete wavelet transforms, and Hilbert-Huang Transform. The ANN algorithm predicts the sepsis patient with 96.7% of accuracy. However, based on the medical requirement for artificial intelligent implementation, this result does not satisfy the requirement as the false positive error is 2.9%.
Co-Authors A K Faizin A K Faizin A Nandini AK Faizin F A Nurmansyah FA Nurmansyah J Sentanuhady M IKHSAN N Adyono N Adyono R D Issafira R D Issafira RD Issafira S D Nurherdiana S Sutiyono Sutardi T P Sari TP Sari W D Lestari W Saputro W Saputro W Wijayanti WD Lestari