Pub Date : 2022-08-28DOI: 10.35335/computational.v11i2.5
Tata Rizky Amalia, Solikhun Solikhun
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.
{"title":"Implementation of the Backpropagation Method to Predict the Percentage of Women as Professionals on the Island of Sumatra","authors":"Tata Rizky Amalia, Solikhun Solikhun","doi":"10.35335/computational.v11i2.5","DOIUrl":"https://doi.org/10.35335/computational.v11i2.5","url":null,"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.","PeriodicalId":330177,"journal":{"name":"International Journal of Mechanical Computational and Manufacturing Research","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123544298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-28DOI: 10.35335/computational.v11i2.6
Yogi Pratama, Solikhun Solikhun
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
{"title":"Determining the Best Performance Using the Backpropagation Algorithm for Expenditure per Capita in North Sumatra","authors":"Yogi Pratama, Solikhun Solikhun","doi":"10.35335/computational.v11i2.6","DOIUrl":"https://doi.org/10.35335/computational.v11i2.6","url":null,"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","PeriodicalId":330177,"journal":{"name":"International Journal of Mechanical Computational and Manufacturing Research","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128595361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-28DOI: 10.35335/computational.v11i2.1
D. Setiawan, Solikhun Solikhun
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.
{"title":"Machine Learning Algorithm for Determining the Best Performance in Predicting Turmeric Production in Indonesia","authors":"D. Setiawan, Solikhun Solikhun","doi":"10.35335/computational.v11i2.1","DOIUrl":"https://doi.org/10.35335/computational.v11i2.1","url":null,"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.","PeriodicalId":330177,"journal":{"name":"International Journal of Mechanical Computational and Manufacturing Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129449351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-28DOI: 10.35335/computational.v11i2.7
Yosua Chandra Simamora, Solikhun Solikhun, Lise Pujiastuti, M. Wahyudi
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
{"title":"Mushroom Production Prediction Model using Conjugate Gradient Algorithm","authors":"Yosua Chandra Simamora, Solikhun Solikhun, Lise Pujiastuti, M. Wahyudi","doi":"10.35335/computational.v11i2.7","DOIUrl":"https://doi.org/10.35335/computational.v11i2.7","url":null,"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","PeriodicalId":330177,"journal":{"name":"International Journal of Mechanical Computational and Manufacturing Research","volume":"6 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131452225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-28DOI: 10.35335/computational.v11i2.3
Oktarihni Haloho, Solikhun Solikhun
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.
{"title":"Artificial Neural Network (ANN) Implementation with Conjugate Gradient Algorithm to Predict Sumatran Melinjo Plant Production","authors":"Oktarihni Haloho, Solikhun Solikhun","doi":"10.35335/computational.v11i2.3","DOIUrl":"https://doi.org/10.35335/computational.v11i2.3","url":null,"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.","PeriodicalId":330177,"journal":{"name":"International Journal of Mechanical Computational and Manufacturing Research","volume":"263 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131473214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：