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INTERNATIONAL JOURNAL OF MECHANICAL COMPUTATIONAL AND MANUFACTURING RESEARCH
Published by Trigin Publisher
ISSN : 23014148     EISSN : 29623391     DOI : 10.35335/MECOMARE
Core Subject : Engineering,
Automotive Engineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering
International Journal of Mechanical Computational And Manufacturing Research invites you to consider submitting original research papers for possible publication after peer review. The scope of this international, scholarly journal is aimed at rapid dissemination of new ideas and techniques and to provide a common forum for significant research and new developments in areas of Mechanical Computational And Manufacturing Research.
Arjuna Subject : Teknik (semua kategori) - Komputasi Mekanik
Articles 95 Documents
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Machine Learning Algorithm for Determining the Best Performance in Predicting Turmeric Production in Indonesia Dendy Setiawan; Solikhun Solikhun
International Journal of Mechanical Computational and Manufacturing Research Vol. 11 No. 2 (2022): August: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (399.263 KB) | DOI: 10.35335/computational.v11i2.1

Abstract

The herb that has many uses in everyday life is turmeric. Not only in Indonesia but in other countries also use turmeric for consumption. Therefore, by making predictions on the level of turmeric production in the country, so that the government or other parties can use this as a reference and reference to solve problems. The method we use is Resilient Backpropagation where this method is one of the methods that is often used to forecast data. By using turmeric plant production data in Indonesia from 2016-2021 taken on the website of the Indonesian Central Statistics Agency. According to the data to be tested a network architecture model is formed, namely 2-15-1, 2-20-1, 2-25- 1 and 2-30-1. From this model, the Fletcher-Reeves method is used. From the 4 models that have been trained and tested, a 2-15-1 model is obtained to be the best architectural model for each method. The accuracy level of the Fletcher-Reeves method with the 2-15-1 model has an MSE value of 0.002481597.
Predicting the Amount of Pineapple Production in Sumatra Using the Fletcher-Reeves Algorithm Hose Fernando Tampubolon; Solikhun Solikhun
International Journal of Mechanical Computational and Manufacturing Research Vol. 11 No. 2 (2022): August: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (550.091 KB) | DOI: 10.35335/computational.v11i2.2

Abstract

Pineapple is a kind of organic product from the Bromeliaceae family which has the logical name Ananas comosus Merr. Pineapple plants have weathered skin and pointed leaves on top. The taste of new pineapple is a combination of sweet and slightly sharp. Pineapple is high in L-ascorbic acid, which helps cells fight damage, according to the Linus Pauling Organization at Oregon State College. L-ascorbic acid is also useful in managing medical conditions, such as heart disease and joint pain. However, due to the absence of consideration from the regions and local governments regarding pineapple on the island of Sumatra, it has caused several problems, especially data on pineapples related to the advantages, content, and uniqueness of pineapples to be used as pineapples. chaotic and diminishing pineapple production, especially on the island of Sumatra. Therefore, it is important to make a wish to know the assessed amount of Pineapple Organic Product Crop Creation on the island of Sumatra so that the public authorities on the island of Sumatra have endlessly clear references to decide on an approach or make major progress sothat the development of pineapple on the island of Sumatra does not diminish. The method used in making predictions is the FletcherReeves algorithm and is a method in ANN. In this study, the data used was the number of pineapple fruit plants on the island of Sumatra in 2012-2021 obtained from BPS. Given this information, organizational design models will not be fully defined, including 4-10-1, 4-15-1, 4-20-1, 4-25-1 and 4-30-1. Of these 5 models, then Training and Testing is done and the best architectural model result is 4-15-1 with the least (less) Performance/MSE test. With the lowest Performance/MSE level of 0.005488189 compared to the other 4 models.
Artificial Neural Network (ANN) Implementation with Conjugate Gradient Algorithm to Predict Sumatran Melinjo Plant Production Oktarihni Haloho; Solikhun Solikhun
International Journal of Mechanical Computational and Manufacturing Research Vol. 11 No. 2 (2022): August: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (535.34 KB) | DOI: 10.35335/computational.v11i2.3

Abstract

Melinjo is an annual plant with open seeds. Tree-shaped and has two houses called dioecious or there are males and females. Melinjo is often found in dry and tropical areas. Indonesia can be one that produces melinjo as a trade product in large quantities. Melinjo is collected and shipped natural products after 5-6 long time after sowing of seeds. In West Sumatra, it is detailed that each year produces 20,000 to 25,000 natural melinjo products and the seed generation reaches 80 to 100 kg per tree per year. Therefore, it is important to know every need for melinjo by anticipating the number of generations of Melinjo using a Manufacturing Artificial Neural System with Backpropagation strategy. With the neural structure made, it will be easier to carry out this investigation. Where the machine learning method can help to find the best performance value and value from the simple data studied. The Matlab2011b application has a feature that helps to calculate the best performance and value with the help of the Conjugate Gradient algorithm. After testing using 5 samples, namely: 4-10-1, 4-15-1, 4-20-1,4-25-1, 4-30-1. Of the five tests, the best results are on data 4-15-1 with the MSE/Performance value of 0.011154591. 4-15-1, 4-20-1,4-25-1, 4-30-1. Of the five tests, the best results are on data 4-15-1 with the MSE/Performance value of 0.011154591. 4-15-1, 4-20-1,4-25-1, 4-30-1. Of the five tests, the best results are on data 4- 15-1 with the MSE/Performance value of 0.011154591.
Implementation of Backpropagation ANN in Predicting Long Bean Crop Production in Sumatra Island Province Zodi Martua Siallagan; Solikhun Solikhun
International Journal of Mechanical Computational and Manufacturing Research Vol. 11 No. 2 (2022): August: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (944.766 KB) | DOI: 10.35335/computational.v11i2.4

Abstract

The production of long bean vegetable crops in Indonesia is very high, this is because this plant is easy to cultivate. Predicting the production of long bean vegetable crops on the island of Sumatra, where the data source comes from BPS (Central Bureau of Statistics). In predicting the use of ANN (Artificial Neural Networks) and the method used in this study is the backpropagation algorithm, this method will be used to predict or predict the production of long bean vegetable crops on the island of Sumatra. The results have been obtained using 4 models, namely the 6-5-1, 6-10-1, 6-15-1, and 6-20-1 models. Among the 4 existing models, the 6-5-1 model has the more accurate accuracy or the lowest error value with an MSE of 0.00711838.
Implementation of the Backpropagation Method to Predict the Percentage of Women as Professionals on the Island of Sumatra Tata Rizky Amalia; Solikhun Solikhun
International Journal of Mechanical Computational and Manufacturing Research Vol. 11 No. 2 (2022): August: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (794.922 KB) | DOI: 10.35335/computational.v11i2.5

Abstract

This study aims to obtain information on the best algorithm from the two algorithms that will be compared based on the smallest/lowest performance value or MSE value, which can later be used as a reference and information for solving women's problems as professional workers on the island of Sumatra. The data used in this study are women as professional workers (percent) 2012-2021 at the Central Statistics Agency (BPS). The algorithm used is Backpropagation Neural Network. Data analysis was carried out using the Artificial Neural Network method using Matlab R2011b(7.13) software. In this review, 5 structural models were used, namely: 4-10-1, 4-15-1, 4-20-1, 4-25-1, 4-30-1, out of five models.
Determining the Best Performance Using the Backpropagation Algorithm for Expenditure per Capita in North Sumatra Yogi Pratama; Solikhun Solikhun
International Journal of Mechanical Computational and Manufacturing Research Vol. 11 No. 2 (2022): August: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (561.067 KB) | DOI: 10.35335/computational.v11i2.6

Abstract

In an effort to maintain per capita income in Indonesia, the Government must take action through strengthening national protection. Per capita is the average income of all residents in a country. Per capita income is obtained from the distribution of the national income of a country by the total population of that country. There is a decrease in the population per capita of North Sumatra at the Central Statistics Agency (BPS) in 2020. The author will use the backpropagation algorithm to make a performance. Backpropagation iskone ofkmethodkartificial neural networklquite reliablejinlsolvekproblem. In researchj5 models are usedlarchitecture: 4-15-1, 4-30-1,k4-45-1, 4-60-1, 4.-75-1, fromjfive modelslThus, the architectural model 4 -75-1 provides the best accuracy withK452 iteration epochs and MSE is 0.00001536
Mushroom Production Prediction Model using Conjugate Gradient Algorithm Yosua Chandra Simamora; Solikhun Solikhun; Lise Pujiastuti; Mochamad Wahyudi
International Journal of Mechanical Computational and Manufacturing Research Vol. 11 No. 2 (2022): August: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (449.464 KB) | DOI: 10.35335/computational.v11i2.7

Abstract

Mushrooms are heterotrophic living things that act as saprophytes on dead plants. Mushrooms contain many important substances such as protein, amino acids, lysine, histidine, etc. Mushrooms tend to be better consumed than animal meat, even the content of lysine and histidine contained in mushrooms is greater than eggs. In recent years the volume of Mushroom Demand has increased, while production has decreased, especially on the island of Sumatra, namely in 2020 and 2021. Therefore, it is necessary to predict the estimated production of mushroom plants on the island of Sumatra so that the government on the island of Sumatra has clear data references to determine policies and make the right steps so that the production of mushroom plants on the island of Sumatra does not continue to decline. The method used in predicting is one of the ANN methods, namely the Conjugate Gradient Algorithm. The data used in this paper is Vegetable Crop Production data from 2014-2021 which was obtained from the website of the Central Statistics Agency. Based on this data, network architecture models such as 3-10-1, 3-15-1, 3-20-1, 3-25-1, 3-30-1, will be formed and defined. From the five models, training and testing values were obtained which showed that the most optimal architectural model was 3-10-1 with a Performance/MSE test value of 0.00055034. This value is the smallest of the 5 architectural models after the training and testing process. From this it can be concluded that this model can be applied to predict mushroom production on the island of Sumatra
Design of A Generator Driven Steam Turbine with A Nominal Power of 10 MW For Industrial Electricity Needs Frans Denny Manurung
International Journal of Mechanical Computational and Manufacturing Research Vol. 9 No. 3 (2020): November: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (754.478 KB)

Abstract

Steam turbine is one type of prime mover that is widely used in industry, including: as a prime mover for electric generators, pumps and compressors, as well as process industries. The things that are considered in the use of the steam turbine are the heat source used to evaporate water can be from gas, liquid, and solid fuels, the efficiency of the steam turbine is greater than the gas turbine. The method used in writing this thesis is as follows: (a) ) Field survey, namely in the form of direct observation to the location where the generating unit is located. (b) Literature study, namely in the form of literature study, study of books, and related writings. (c) Discussion, which is in the form of questions and answers with the supervisor, The comparison lecturer who will be appointed by the Department of Cylindrical Mechanical Engineering for small and medium capacity turbines is usually made of gray cast iron JIS G 5501 FC30 with a tensile stress of b 27 kg/mm2 or 2700 kg/cm2 and a safety factor value of k3 (taken) so : b permit 4000/3 1333,33kg/cm2 thus : b permit t , then this construction is safe. From the calculations performed, some conclusions can be drawn in the design of the steam turbine driving the generator: 6.1. Specifications of steam turbine 1. Inlet steam pressure : 42 bar 2. Turbine inlet steam temperature : 480 0 C 3. Turbine outlet steam pressure : 0.1 bar 4. Turbine level : 10 level 5. Extraction amount : 1 level 6. Flow rate steam mass : 12,163 kg/s 7. Turbine power : 12,47 MW 8. Turbine Shaft rotation : 5700 rpm 6.2. Dimensions of the main parts of the turbine: 1.
Design and Build Mini Alcohol Distillation Equipment from Nira Aren Yasin Suhartono
International Journal of Mechanical Computational and Manufacturing Research Vol. 9 No. 3 (2020): November: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (419.253 KB)

Abstract

Palm sap is a sweet liquid obtained from the sugar palm plant (Arenga pinnata MEER) by cutting the flower stalk. Generally, palm sap is widely used for the manufacture of brown sugar, fresh drink of palm sap (saguer), vinegar and alcoholic beverages. The model planned for the manufacture of this distillation is water distillation, where the accommodated palm juice is placed in a container that is in direct contact with heating water, then the juice vapor is passed through a pipe which is then condensed through a condenser and the results are accommodated through an alcohol container. over H2O (water) and alcohol, because the difference in boiling temperature where the boiling temperature of water is higher so that at a temperature of 87 C which is the boiling temperature of the alcohol will evaporate first while the water has not undergone the evaporation process. So the pump efficiency is 91.6%. From the results of the calculation of the design of palm juice distalization, the following conclusions can be drawn: Construction of Distalation Capacity: 5 liters Heating media: Stove for kerosene materials Distallation model: Distillation with water, equipped with a condenser Skeleton Material: Iron profile plate 40 Base material: 12 mm plywood board Condenser water tank Size : 300 mm × 300 mm × 300 mm Material : 0.7 mm zinc plate University of North Sumatra.
The Test of Alcohol Distallation Equipment from A Mix of Palm Sap with Coconut Shell Charcoal and Lime Giarman Giarman
International Journal of Mechanical Computational and Manufacturing Research Vol. 10 No. 4 (2022): February: Mechanical Computational And Manufacturing Research
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (476.132 KB)

Abstract

Palm sap is a sweet liquid obtained from the sugar palm plant (Arenga pinnata MEER) by cutting the flower stalk. Generally, palm sap is widely used for the manufacture of brown sugar, fresh drink of palm sap (saguer), vinegar and alcoholic beverages. The testing procedure carried out is as follows: Beginning of the test 1. Recording the air temperature 2. Recording the temperature of the water and palm sap 3. Heating is done using a kerosene stove with an estimated temperature of up to 100 C boiling. A total of 5 liters of palm sap raw material is put into the heating tank which is flowed through the top hole by opening the cover, accompanied by filling water in the heating tank. On checking the level of purity with the influence of coconut shell charcoal powder as an absorbent on palm sap alcohol, it was seen that there was an effect in increasing alcohol content. However, it cannot be completely absorbed considering that the coconut shell charcoal used is not active coconut shell charcoal. To produce a good level of alcohol purity (80%) a good mixture ratio is 150 grams: 50 grams of coconut shell charcoal and lime. The efficiency of distalization is 83%. 50 grams of coconut shell charcoal and lime. The efficiency of distalization is 83%. 50 grams of coconut shell charcoal and lime. The efficiency of distalization is 83%.

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