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Tritiya Arungpadang
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Automotive Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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ANALISIS KEKUATAN POROS LANDING GEAR PESAWAT N-219 Nizar Malendes; Stenly Tangkuman; Tritiya Arungpadang
JURNAL POROS TEKNIK MESIN UNSRAT Vol. 5 No. 2 (2016): Jurnal Poros Teknik Mesin Unsrat
Publisher : Fakultas Teknik Jurusan Teknik Mesin Universitas Sam Ratulangi

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The aim of this study is to analyze the strength of the shaft of the landing gear aircraft N-219 against the variation of cargo’s weight. The examined object in this study is the landing gear of N-219 aircraft produced by PT Dirgantara Indonesia. The static strength analysis was conducted on the stress and maximum deflection to the shaft of the landing gear N-219 aircraft. The results of this study showed that the variation of cargo’s weight affects the strength of the landing gear shaft where the increase of the cargo’s weight will result in a linear increase of deflection and stress. Finally, the allowed maximum weight of the N-219 aircraft cargo is 2500 kg with the landing gear shaft deflection of 0,00164 meter and the stress of 298 MPa. Simulation in this study was conducted by using ANSYS 2014, where this software provides load, deflection and stress analysis. It is found that the analysis of manual calculation and software-based calculation shows only little difference.   Keywords : Aircraft N-219, Landing Gear, Shaft, Strenght analyze
ESTIMASI BEBAN PUNCAK ENERGI LISTRIK PADA SISTEM SULUTGO MENGGUNAKAN ARTIFICIAL NEURAL NETWORK DAN METODE MOVING AVERAGE Liberty Tarigan; Tritiya Arungpadang; Johan S C Neyland
JURNAL POROS TEKNIK MESIN UNSRAT Vol. 5 No. 2 (2016): Jurnal Poros Teknik Mesin Unsrat
Publisher : Fakultas Teknik Jurusan Teknik Mesin Universitas Sam Ratulangi

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Sulutgo interconnection system is the electrical energy suppliers for North Sulawesi and Gorontalo. Their role as the electrical energy supplier was complained by people in 2015, due to lack of electricity supply that lead to continuous rolling blackouts. Accordingly, it is important to identify the electrical peak load in Sulutgo system, so that the electrical necessity of the people can be properly fulfilled. The electrical peak load in the next 12 month is estimated using the backpropagation method artificial neural network and forecasting method moving average. The estimation was performed by using the last 24 month peak load data. Based on the results of both estimation, it is found the backpropagation method artificial neural network has fluctuated results while the forecasting method moving average gives stable results. The results of the estimation of peak load electricity using bacpropagation  artificial neural network method for the next 12 month starting from July 2016 to June 2017 are 327.48, 353.99, 316.32, 316.66, 332.37, 329.79, 332.31, 356.21, 318.60, 349.56, 351.37, 362.04 MW. While the results of the estimation method using moving average forecasting for the same period are 325.68, 326.03, 326.39, 326.72, 327.25, 328.09, 327.94, 328.72, 329.94, 330.32, 327.65, 326.52 MW.   Keywords: Estimation, Artificial Neural Network, Forecast Method Moving Average
PREDIKSI KEBUTUHAN ENERGI LISTRIK SULAWESI UTARA MENGGUNAKAN ARTIFICIAL NEURAL NETWORK DAN METODE EXPONENTIAL SMOOTHING Febry Aprily Hontong; Tritiya Arungpadang; Johan S C Neyland
JURNAL POROS TEKNIK MESIN UNSRAT Vol. 5 No. 2 (2016): Jurnal Poros Teknik Mesin Unsrat
Publisher : Fakultas Teknik Jurusan Teknik Mesin Universitas Sam Ratulangi

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To predict the electrical energy need of North Sulawesi for one year ahead requires correct methods. The reliable methods used for the prediction task in this research are Artificial Neural Network and Exponential Smoothing. The prediction results using Artificial Neural Network are 110.38, 112.62, 111.56, 108.05, 107.95, 110.32, 109.90, 110.58, 113.26, 107.11, 115.60, 105.40 GWh. The prediction results using Exponential Smoothing are 112.32, 112.70, 113.07, 113.45, 113.82, 114.19, 114.57, 114.94, 115.32, 115.69, 116.07, 116.44 GWh.   Key words: Artificial Neural Network, Exponential Smoothing, Prediction, Electrical Energy Need.
PREDIKSI KEBUTUHAN ENERGI LISTRIK DI SULAWESI UTARA : SEBUAH STRATEGI IMPLEMENTASI Raymond Lumintang; Tritiya Arungpadang; Charles Ch Punuhsingon
JURNAL POROS TEKNIK MESIN UNSRAT Vol. 7 No. 1 (2018): Jurnal Poros Teknik Mesin Unsrat
Publisher : Fakultas Teknik Jurusan Teknik Mesin Universitas Sam Ratulangi

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      The purpose of this research is to design the implementation strategy of electric energy requirement in sulawesi uatra by using SWOT analysis. Method of auxiliary devices used as a tool tool aids electrical energy demand analysis using artificial neural network analysis. From SWOT analysis result, SWOT parameter values are: Strength 1.65, Weaknesses 0.95, Opportunity 1.75, Threats 1.05.            The results of the SWOT analysis show that the types of threats that must be considered is the uncertainty of primary energy, especially gas, and the weakness is the limited power and networks that have not been able to reach the suluttenggo region especially the archipelago.Keywords: SWOT Analysis, Design Implementation Strategy, Prediction Electrical                   Energy Requirement
ALISIS SIFAT MEKANIK RANTAI TIPE 428 PADA SEPEDA MOTOR PRODUK YAMAHA MX135 Brilliant Davidson; Markus Karamoy Umboh; Tritiya Arungpadang
JURNAL POROS TEKNIK MESIN UNSRAT Vol. 10 No. 2 (2021): Jurnal Poros Teknik Mesin Unsrat
Publisher : Fakultas Teknik Jurusan Teknik Mesin Universitas Sam Ratulangi

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The motorcycle chain is one of the most important parts of the motor which has a function to transmit power from the engine to the wheels. In this study, an analysis of the mechanical properties and chemical composition of the plates and pins of the Yamaha MX 135 type 428 motorcycle chain and other motorcycle chain products was carried out. The methodology used is hardness testing, microstructure testing and chemical composition testing on the two motor chain products and comparing them with the standard.The results obtained show that the chain plate hardness value for Yamaha products is 44.35HRC and other products of 44.4 HRC have exceeded the SAE 1050 hardness standard of 30 HRC. The hardness value of the Yamaha motorcycle chain pin is 427 HB and the motorcycle chain pin of other products is 428 HB which has met the AISI 15B25 standard of 131 HB. Thus, the value of the tensile strength of both plate and chain pins for Yamaha motorcycles and other products obtained from the conversion of hardness values also exceeds the set standards. The results of microstructure testing for plates and pins of motorcycle chains for Yamaha products and other products contain ferrite and pearlite phases with uneven distribution. The results of the chemical composition test show that the Yamaha motorcycle chain plate has met the SAE 1050 standard while the other product motorcycle chain has a C element content of 1.44% exceeding the standard which is 0.48-0.55%. In the motorcycle chain pin, Yamaha products have a C content of 0.4% and in other products it has a C content of 0.43%, which is greater than the AISI 15B25 standard of 0.22-0.3% C.
Perancangan Rotor Turbin Angin Savonius Tipe-L Untuk Pembangkit Listrik Pada Rumah Tinggal Woe Junior; Stenly Tangkuman; Tritiya Arungpadang
JURNAL POROS TEKNIK MESIN UNSRAT Vol. 11 No. 1 (2022): Jurnal Poros Teknik Mesin Unsrat
Publisher : Fakultas Teknik Jurusan Teknik Mesin Universitas Sam Ratulangi

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Rotor is one of the main component in wind power plant. The rotor plays a role in converting wind energy into rotary energy / mechanical energy. To connect the rotor to the gear requires a shaft. This research aims to design a rotor Savonius Wind Turbine with an L blade type for a Wind Power Plant. This research has two purposes, first to design the Rotor Savonius Wind Turbine and then simulate the rotor in the Ansys Workbench 18.1 to sees the output power. Second is making a Rotor to complete a miniature Wind Power Plant with a ratio of 1:5.             The result of the Rotor design is that the diameter is 1.25 m and the height is 2.5 m. Can operate at 6.25 m/s with the output power is 120 Watt. The rotor miniature can function properly and has been installed on a miniature Wind Power Plant. Keywords: Rotor, Wind Power Plant
Pendekatan Dual Response Pada Prediksi Penjualan Sepeda Motor Menggunakan Jaringan Syaraf Tiruan Chan Makarewa; Tritiya Arungpadang; Jefferson Mende
JURNAL POROS TEKNIK MESIN UNSRAT Vol. 11 No. 2 (2022): Jurnal Poros Teknik Mesin Unsrat
Publisher : Fakultas Teknik Jurusan Teknik Mesin Universitas Sam Ratulangi

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Dual response approach is using for get the maximal result of prediction on Neural Network, in order to prediction motorcycle sale in the next period. The purpose of the research is (1) to make model of motorcycle prediction using neural network, and (2) make prediction and analyze the result of motorcycle prediction. First step to do in this research is searching the mean and standard deviation from the historycal data which obtained. And then data is normalized to the sigmoid biner form, with range from 0,1 to 0,9. After that train the data to recognize the pattern through the training process and testing process. And the next step for simulation process to get the prediction result. Result from the research which using the train function “trainlm” with network architecture 12-8-3-2 from january 2021 until december 2021 is; 302, 284, 326, 253, 277, 277, 240, 296, 284, 275, 265, and 310. The prediction result is showing that highest sales is on march 2021 with 326 motorcycle unit, and the lowest sales is on july 2021 with only 240 motorcycle unit. The prediction showing us sales drop because of the covid-19 pandemic. Keywords : Prediction, dual response, neural network
Co-Authors Brilliant Davidson Chan Makarewa Charles Ch Punuhsingon Febry Aprily Hontong Jefferson Mende Johan S C Neyland Liberty Tarigan Markus Karamoy Umboh Nizar Malendes Raymond Lumintang Stenly Tangkuman Woe Junior