PROCEEDINGS OF THE 8TH SEAMS-UGM INTERNATIONAL CONFERENCE ON MATHEMATICS AND ITS APPLICATIONS 2019: Deepening Mathematical Concepts for Wider Application through Multidisciplinary Research and Industries Collaborations最新文献
The DL-integral is a Riemann-type integral which is given in [2,4]. The uniqueness of the DL-integral and the relation between the DL-integral and the Henstock integral has already been discussed in [4] but did not discuss the properties and the convergence theorems of the DL-integral. Therefore, we prove the basic properties and some convergence theorems of the DL-integral.The DL-integral is a Riemann-type integral which is given in [2,4]. The uniqueness of the DL-integral and the relation between the DL-integral and the Henstock integral has already been discussed in [4] but did not discuss the properties and the convergence theorems of the DL-integral. Therefore, we prove the basic properties and some convergence theorems of the DL-integral.
{"title":"Basic properties and some convergence theorems of the DL-integral","authors":"Mufti Al Ummam, C. R. Indrati","doi":"10.1063/1.5139146","DOIUrl":"https://doi.org/10.1063/1.5139146","url":null,"abstract":"The DL-integral is a Riemann-type integral which is given in [2,4]. The uniqueness of the DL-integral and the relation between the DL-integral and the Henstock integral has already been discussed in [4] but did not discuss the properties and the convergence theorems of the DL-integral. Therefore, we prove the basic properties and some convergence theorems of the DL-integral.The DL-integral is a Riemann-type integral which is given in [2,4]. The uniqueness of the DL-integral and the relation between the DL-integral and the Henstock integral has already been discussed in [4] but did not discuss the properties and the convergence theorems of the DL-integral. Therefore, we prove the basic properties and some convergence theorems of the DL-integral.","PeriodicalId":209108,"journal":{"name":"PROCEEDINGS OF THE 8TH SEAMS-UGM INTERNATIONAL CONFERENCE ON MATHEMATICS AND ITS APPLICATIONS 2019: Deepening Mathematical Concepts for Wider Application through Multidisciplinary Research and Industries Collaborations","volume":"39 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121009936","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}
Natural disasters are events that threaten and disrupt the lives and livelihoods of people caused by natural factors. Indonesia is a country prone to natural disasters. This is triggered by its geographical position flanked by two large oceans and geologically at the confluence of the three main plates. One way to reduce the impact of natural disasters is to mitigate hazards. Mitigation will reduce the negative impact caused by disasters, especially for residents. It can also be a guideline for development planning. The way of mitigation efforts can be done by introducing and monitoring disaster risk. For example, to observe what factors affect the level of building damage caused by a disaster. We can do this with the Bayesian Network approach because this approach provides flexibility in seeing relationships between variables and adding new variables based on expert analysis. These advantages are very supportive related to cases of natural disasters; sometimes, there are often developments in variables that affect the level of damage in the field. The first step in the approach is to form a structure. In this study, we conducted two types of structure formation, namely using the Naive Bayes algorithm and expert opinion. From these two methods, the creation of a structure based on expert opinion is more accurate.
{"title":"Disaster mitigation solutions with Bayesian network","authors":"D. P. Sari, D. Rosadi, A. R. Effendie, Danardono","doi":"10.1063/1.5139178","DOIUrl":"https://doi.org/10.1063/1.5139178","url":null,"abstract":"Natural disasters are events that threaten and disrupt the lives and livelihoods of people caused by natural factors. Indonesia is a country prone to natural disasters. This is triggered by its geographical position flanked by two large oceans and geologically at the confluence of the three main plates. One way to reduce the impact of natural disasters is to mitigate hazards. Mitigation will reduce the negative impact caused by disasters, especially for residents. It can also be a guideline for development planning. The way of mitigation efforts can be done by introducing and monitoring disaster risk. For example, to observe what factors affect the level of building damage caused by a disaster. We can do this with the Bayesian Network approach because this approach provides flexibility in seeing relationships between variables and adding new variables based on expert analysis. These advantages are very supportive related to cases of natural disasters; sometimes, there are often developments in variables that affect the level of damage in the field. The first step in the approach is to form a structure. In this study, we conducted two types of structure formation, namely using the Naive Bayes algorithm and expert opinion. From these two methods, the creation of a structure based on expert opinion is more accurate.","PeriodicalId":209108,"journal":{"name":"PROCEEDINGS OF THE 8TH SEAMS-UGM INTERNATIONAL CONFERENCE ON MATHEMATICS AND ITS APPLICATIONS 2019: Deepening Mathematical Concepts for Wider Application through Multidisciplinary Research and Industries Collaborations","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122071606","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}
The Vehicle Routing Problem (VRP) is an extension of the Traveling Salesman Problem (TSP). It can be expanded into the vehicle routing problem with pick-up and delivery (VRP-PD). One of the current real problem is that there are drivers in various places to serve customers by picking up and shipping goods to/from their location within the same day. As this service gaining its popularity, more and more customers must be served making it necessary to determine the efficient and effective vehicle routes for simultaneous pickup and delivery activities. This study proposes a genetic algorithm-based approach to this problem. An example problem is conducted to assess its practicality before real problems application.The Vehicle Routing Problem (VRP) is an extension of the Traveling Salesman Problem (TSP). It can be expanded into the vehicle routing problem with pick-up and delivery (VRP-PD). One of the current real problem is that there are drivers in various places to serve customers by picking up and shipping goods to/from their location within the same day. As this service gaining its popularity, more and more customers must be served making it necessary to determine the efficient and effective vehicle routes for simultaneous pickup and delivery activities. This study proposes a genetic algorithm-based approach to this problem. An example problem is conducted to assess its practicality before real problems application.
{"title":"Vehicle routing problem with pick-up and deliveries using genetic algorithm in express delivery services","authors":"Stacia Gunawan, N. Susyanto, Syafri Bahar","doi":"10.1063/1.5139155","DOIUrl":"https://doi.org/10.1063/1.5139155","url":null,"abstract":"The Vehicle Routing Problem (VRP) is an extension of the Traveling Salesman Problem (TSP). It can be expanded into the vehicle routing problem with pick-up and delivery (VRP-PD). One of the current real problem is that there are drivers in various places to serve customers by picking up and shipping goods to/from their location within the same day. As this service gaining its popularity, more and more customers must be served making it necessary to determine the efficient and effective vehicle routes for simultaneous pickup and delivery activities. This study proposes a genetic algorithm-based approach to this problem. An example problem is conducted to assess its practicality before real problems application.The Vehicle Routing Problem (VRP) is an extension of the Traveling Salesman Problem (TSP). It can be expanded into the vehicle routing problem with pick-up and delivery (VRP-PD). One of the current real problem is that there are drivers in various places to serve customers by picking up and shipping goods to/from their location within the same day. As this service gaining its popularity, more and more customers must be served making it necessary to determine the efficient and effective vehicle routes for simultaneous pickup and delivery activities. This study proposes a genetic algorithm-based approach to this problem. An example problem is conducted to assess its practicality before real problems application.","PeriodicalId":209108,"journal":{"name":"PROCEEDINGS OF THE 8TH SEAMS-UGM INTERNATIONAL CONFERENCE ON MATHEMATICS AND ITS APPLICATIONS 2019: Deepening Mathematical Concepts for Wider Application through Multidisciplinary Research and Industries Collaborations","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121979714","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}
One of the fundamental problems in mathematical finance is the pricing of derivative assets such as options. In practice, pricing an exotic option, whose value depends on the price evolution of an underlying risky asset, requires a model and then numerical simulations. Having no a priori model for the risky asset, but only the knowledge of its distribution at certain times, we instead look for a lower bound for the option price using the Monge-Kantorovich transportation theory. In this paper, we consider the Monge-Kantorovich problem that is restricted over the set of martingale measure. In order to solve such problem, we first look at sufficient conditions for the existence of an optimal martingale measure. Next, we focus our attention on problems with transports which are two-dimensional real martingale measures with uniform marginals. We then come up with some characterization of the optimizer, using measure-quantization approach.
{"title":"On the restriction of the optimal transportation problem to the set of martingale measures with uniform marginals","authors":"J. M. L. Escaner, D. Saddi, J. Salazar","doi":"10.1063/1.5139152","DOIUrl":"https://doi.org/10.1063/1.5139152","url":null,"abstract":"One of the fundamental problems in mathematical finance is the pricing of derivative assets such as options. In practice, pricing an exotic option, whose value depends on the price evolution of an underlying risky asset, requires a model and then numerical simulations. Having no a priori model for the risky asset, but only the knowledge of its distribution at certain times, we instead look for a lower bound for the option price using the Monge-Kantorovich transportation theory. In this paper, we consider the Monge-Kantorovich problem that is restricted over the set of martingale measure. In order to solve such problem, we first look at sufficient conditions for the existence of an optimal martingale measure. Next, we focus our attention on problems with transports which are two-dimensional real martingale measures with uniform marginals. We then come up with some characterization of the optimizer, using measure-quantization approach.","PeriodicalId":209108,"journal":{"name":"PROCEEDINGS OF THE 8TH SEAMS-UGM INTERNATIONAL CONFERENCE ON MATHEMATICS AND ITS APPLICATIONS 2019: Deepening Mathematical Concepts for Wider Application through Multidisciplinary Research and Industries Collaborations","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130471166","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}
In this paper, we propose a new technique in solving the minimum of a function defined on a ball centered at x0 with radius ρ¯ using successive implementations of Golden Search algorithm. We show numerically that our proposed method can effectively approximate the minimum of a function even if it is nonsmooth or discontinuous. We also introduce partitioning to estimate the global minimum of multimodal functions. Furthermore, we compare the performance of SGS with Simulated Annealing in estimating the global minimum of a set of multimodal functions. Lastly, we apply our method to estimate the parameters of a physiological system.
{"title":"An unconstrained minimization technique using successive implementations of Golden Search algorithm","authors":"P. Salonga, Jose Marie Inaudito, R. Mendoza","doi":"10.1063/1.5139164","DOIUrl":"https://doi.org/10.1063/1.5139164","url":null,"abstract":"In this paper, we propose a new technique in solving the minimum of a function defined on a ball centered at x0 with radius ρ¯ using successive implementations of Golden Search algorithm. We show numerically that our proposed method can effectively approximate the minimum of a function even if it is nonsmooth or discontinuous. We also introduce partitioning to estimate the global minimum of multimodal functions. Furthermore, we compare the performance of SGS with Simulated Annealing in estimating the global minimum of a set of multimodal functions. Lastly, we apply our method to estimate the parameters of a physiological system.","PeriodicalId":209108,"journal":{"name":"PROCEEDINGS OF THE 8TH SEAMS-UGM INTERNATIONAL CONFERENCE ON MATHEMATICS AND ITS APPLICATIONS 2019: Deepening Mathematical Concepts for Wider Application through Multidisciplinary Research and Industries Collaborations","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115015034","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}
In this paper, we propose mathematical models to describe the behavior of deposit and loan volumes between two banks via logistic model. There are four models that represent the combination of saving and debt transfer between two banks. The parameters values of each model are estimated using the spiral optimization algorithm based on monthly data on deposit and loan volumes of two groups of commercial banks in Indonesia. The results give the solution of the models that can fit the data well. In the long run, the amount of deposit and loan will go to their equilibrium values but each model has different behaviors due to the impact of the transfer factors.In this paper, we propose mathematical models to describe the behavior of deposit and loan volumes between two banks via logistic model. There are four models that represent the combination of saving and debt transfer between two banks. The parameters values of each model are estimated using the spiral optimization algorithm based on monthly data on deposit and loan volumes of two groups of commercial banks in Indonesia. The results give the solution of the models that can fit the data well. In the long run, the amount of deposit and loan will go to their equilibrium values but each model has different behaviors due to the impact of the transfer factors.
{"title":"Logistic models of deposit and loan between two banks with saving and debt transfer factors","authors":"Moch. Fandi Ansori, K. A. Sidarto, N. Sumarti","doi":"10.1063/1.5139148","DOIUrl":"https://doi.org/10.1063/1.5139148","url":null,"abstract":"In this paper, we propose mathematical models to describe the behavior of deposit and loan volumes between two banks via logistic model. There are four models that represent the combination of saving and debt transfer between two banks. The parameters values of each model are estimated using the spiral optimization algorithm based on monthly data on deposit and loan volumes of two groups of commercial banks in Indonesia. The results give the solution of the models that can fit the data well. In the long run, the amount of deposit and loan will go to their equilibrium values but each model has different behaviors due to the impact of the transfer factors.In this paper, we propose mathematical models to describe the behavior of deposit and loan volumes between two banks via logistic model. There are four models that represent the combination of saving and debt transfer between two banks. The parameters values of each model are estimated using the spiral optimization algorithm based on monthly data on deposit and loan volumes of two groups of commercial banks in Indonesia. The results give the solution of the models that can fit the data well. In the long run, the amount of deposit and loan will go to their equilibrium values but each model has different behaviors due to the impact of the transfer factors.","PeriodicalId":209108,"journal":{"name":"PROCEEDINGS OF THE 8TH SEAMS-UGM INTERNATIONAL CONFERENCE ON MATHEMATICS AND ITS APPLICATIONS 2019: Deepening Mathematical Concepts for Wider Application through Multidisciplinary Research and Industries Collaborations","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125318982","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}
J. D. Urrutia, Alsafat M. Abdul, Jacky Boy E. Atienza
In this research, Autoregressive Integrated Moving Average (ARIMA) and Bayesian Artificial Neural Network (BANN) were used in forecasting the imports and exports of the Philippines and the comparison of two models are one of the main objective of this research. The data were gathered from Philippines Statistical Authority with a total of 100 observations from the first quarter of 1993 to fourth quarter of 2017. Furthermore, it can be determined in this research the best fit among the models in forecasting the imports and exports of the Philippines and the researchers will give the forecast values of imports and exports from the first quarter of year 2018 to the fourth quarter of year 2022 using the most fitted model. The researchers conducted a Statistical test in order to formulate and compare the statistical models of ARIMA and BANN for imports and exports then applied the forecasting accuracy such as MSE, NMSE, MAE, RMSE, and MAPE to compare the performance of the two models. By comparing the results, the researchers concluded that Bayesian Artificial Neural Network is the most fitted model in forecasting the imports and export of the Philippines. Upon using the Paired T-test, the p-value for both imports and exports are greater than the level of significance (α = 0.01) which means that there is no significant difference between actual and predicted values for both imports and exports of the Philippines. This study could help the economy of the Philippines by considering the forecasted Imports and Exports which can be used in analyzing the economy’s trade deficit.In this research, Autoregressive Integrated Moving Average (ARIMA) and Bayesian Artificial Neural Network (BANN) were used in forecasting the imports and exports of the Philippines and the comparison of two models are one of the main objective of this research. The data were gathered from Philippines Statistical Authority with a total of 100 observations from the first quarter of 1993 to fourth quarter of 2017. Furthermore, it can be determined in this research the best fit among the models in forecasting the imports and exports of the Philippines and the researchers will give the forecast values of imports and exports from the first quarter of year 2018 to the fourth quarter of year 2022 using the most fitted model. The researchers conducted a Statistical test in order to formulate and compare the statistical models of ARIMA and BANN for imports and exports then applied the forecasting accuracy such as MSE, NMSE, MAE, RMSE, and MAPE to compare the performance of the two models. By comparing the results, ...
{"title":"Forecasting Philippines imports and exports using Bayesian artificial neural network and autoregressive integrated moving average","authors":"J. D. Urrutia, Alsafat M. Abdul, Jacky Boy E. Atienza","doi":"10.1063/1.5139185","DOIUrl":"https://doi.org/10.1063/1.5139185","url":null,"abstract":"In this research, Autoregressive Integrated Moving Average (ARIMA) and Bayesian Artificial Neural Network (BANN) were used in forecasting the imports and exports of the Philippines and the comparison of two models are one of the main objective of this research. The data were gathered from Philippines Statistical Authority with a total of 100 observations from the first quarter of 1993 to fourth quarter of 2017. Furthermore, it can be determined in this research the best fit among the models in forecasting the imports and exports of the Philippines and the researchers will give the forecast values of imports and exports from the first quarter of year 2018 to the fourth quarter of year 2022 using the most fitted model. The researchers conducted a Statistical test in order to formulate and compare the statistical models of ARIMA and BANN for imports and exports then applied the forecasting accuracy such as MSE, NMSE, MAE, RMSE, and MAPE to compare the performance of the two models. By comparing the results, the researchers concluded that Bayesian Artificial Neural Network is the most fitted model in forecasting the imports and export of the Philippines. Upon using the Paired T-test, the p-value for both imports and exports are greater than the level of significance (α = 0.01) which means that there is no significant difference between actual and predicted values for both imports and exports of the Philippines. This study could help the economy of the Philippines by considering the forecasted Imports and Exports which can be used in analyzing the economy’s trade deficit.In this research, Autoregressive Integrated Moving Average (ARIMA) and Bayesian Artificial Neural Network (BANN) were used in forecasting the imports and exports of the Philippines and the comparison of two models are one of the main objective of this research. The data were gathered from Philippines Statistical Authority with a total of 100 observations from the first quarter of 1993 to fourth quarter of 2017. Furthermore, it can be determined in this research the best fit among the models in forecasting the imports and exports of the Philippines and the researchers will give the forecast values of imports and exports from the first quarter of year 2018 to the fourth quarter of year 2022 using the most fitted model. The researchers conducted a Statistical test in order to formulate and compare the statistical models of ARIMA and BANN for imports and exports then applied the forecasting accuracy such as MSE, NMSE, MAE, RMSE, and MAPE to compare the performance of the two models. By comparing the results, ...","PeriodicalId":209108,"journal":{"name":"PROCEEDINGS OF THE 8TH SEAMS-UGM INTERNATIONAL CONFERENCE ON MATHEMATICS AND ITS APPLICATIONS 2019: Deepening Mathematical Concepts for Wider Application through Multidisciplinary Research and Industries Collaborations","volume":"237 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114414456","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}
The lack of the number of observations raises difficulty in estimating all possible main effects, as well as interaction effects, in the analysis of supersaturated experiments because the number of effects exceed the experiment size. There are some available methods in the literature. However they mostly deal with main effects only. In fact, the existence of confounding between main and interaction effects could lead to a misconclusion that a main effect is active but the true one is the interaction that is confounding with. Our novel approach employing genetic algorithm could simultaneously select appropriate main and interaction effects by considering the heredity principle. We implemented the approach to some data available in literature and revealed some good and useful results. The approach works with binary chromosomes representation with some restrictions to include corresponded main effects whenever the interaction is in the model.The lack of the number of observations raises difficulty in estimating all possible main effects, as well as interaction effects, in the analysis of supersaturated experiments because the number of effects exceed the experiment size. There are some available methods in the literature. However they mostly deal with main effects only. In fact, the existence of confounding between main and interaction effects could lead to a misconclusion that a main effect is active but the true one is the interaction that is confounding with. Our novel approach employing genetic algorithm could simultaneously select appropriate main and interaction effects by considering the heredity principle. We implemented the approach to some data available in literature and revealed some good and useful results. The approach works with binary chromosomes representation with some restrictions to include corresponded main effects whenever the interaction is in the model.
{"title":"Alternative approach to identify active effects in supersaturated experiments","authors":"A. Safitri, R. Anisa, B. Sartono","doi":"10.1063/1.5139177","DOIUrl":"https://doi.org/10.1063/1.5139177","url":null,"abstract":"The lack of the number of observations raises difficulty in estimating all possible main effects, as well as interaction effects, in the analysis of supersaturated experiments because the number of effects exceed the experiment size. There are some available methods in the literature. However they mostly deal with main effects only. In fact, the existence of confounding between main and interaction effects could lead to a misconclusion that a main effect is active but the true one is the interaction that is confounding with. Our novel approach employing genetic algorithm could simultaneously select appropriate main and interaction effects by considering the heredity principle. We implemented the approach to some data available in literature and revealed some good and useful results. The approach works with binary chromosomes representation with some restrictions to include corresponded main effects whenever the interaction is in the model.The lack of the number of observations raises difficulty in estimating all possible main effects, as well as interaction effects, in the analysis of supersaturated experiments because the number of effects exceed the experiment size. There are some available methods in the literature. However they mostly deal with main effects only. In fact, the existence of confounding between main and interaction effects could lead to a misconclusion that a main effect is active but the true one is the interaction that is confounding with. Our novel approach employing genetic algorithm could simultaneously select appropriate main and interaction effects by considering the heredity principle. We implemented the approach to some data available in literature and revealed some good and useful results. The approach works with binary chromosomes representation with some restrictions to include corresponded main effects whenever the interaction is in the model.","PeriodicalId":209108,"journal":{"name":"PROCEEDINGS OF THE 8TH SEAMS-UGM INTERNATIONAL CONFERENCE ON MATHEMATICS AND ITS APPLICATIONS 2019: Deepening Mathematical Concepts for Wider Application through Multidisciplinary Research and Industries Collaborations","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116677594","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}
Hermansah, D. Rosadi, Herni Utami, Abdurakhman, G. Darmawan
In this research, we propose a hybrid MODWT-FFNN model for non-stationary and Long-Range Dependence (LRD) of time series data. The hybrid MODWT-FFNN model is a combination of the Maximal Overlap Discrete Wavelet Transform (MODWT) and the Feed-Forward Neural Network (FFNN) models. The decomposition of time series data using the MODWT model will produce wavelet (detail) and scale (smooth) coefficients. The detail and smooth coefficients are then estimated using the FFNN model. The final result of time series data forecasting obtained from the combined forecast value of the detail and smooth coefficients. In the case study of daily Rainfall data in Aceh, the Root Mean Squared Error (RMSE) and Median Absolute Deviation (MAD) values obtained by our model are smaller than those of the ARIMA, exponential smoothing, and MODWT-ARMA models. The second case study of the Jakarta Stock Exchange Composite (JKSE) daily data, obtained the smallest RMSE and MAD values in the hybrid MODWT-ARMA model, the model we propose is in the second number. This indicates that the hybrid MODWT-FFNN model is useful for adding forecasting accuracy to seasonal data patterns.
{"title":"Hybrid MODWT-FFNN model for time series data forecasting","authors":"Hermansah, D. Rosadi, Herni Utami, Abdurakhman, G. Darmawan","doi":"10.1063/1.5139175","DOIUrl":"https://doi.org/10.1063/1.5139175","url":null,"abstract":"In this research, we propose a hybrid MODWT-FFNN model for non-stationary and Long-Range Dependence (LRD) of time series data. The hybrid MODWT-FFNN model is a combination of the Maximal Overlap Discrete Wavelet Transform (MODWT) and the Feed-Forward Neural Network (FFNN) models. The decomposition of time series data using the MODWT model will produce wavelet (detail) and scale (smooth) coefficients. The detail and smooth coefficients are then estimated using the FFNN model. The final result of time series data forecasting obtained from the combined forecast value of the detail and smooth coefficients. In the case study of daily Rainfall data in Aceh, the Root Mean Squared Error (RMSE) and Median Absolute Deviation (MAD) values obtained by our model are smaller than those of the ARIMA, exponential smoothing, and MODWT-ARMA models. The second case study of the Jakarta Stock Exchange Composite (JKSE) daily data, obtained the smallest RMSE and MAD values in the hybrid MODWT-ARMA model, the model we propose is in the second number. This indicates that the hybrid MODWT-FFNN model is useful for adding forecasting accuracy to seasonal data patterns.","PeriodicalId":209108,"journal":{"name":"PROCEEDINGS OF THE 8TH SEAMS-UGM INTERNATIONAL CONFERENCE ON MATHEMATICS AND ITS APPLICATIONS 2019: Deepening Mathematical Concepts for Wider Application through Multidisciplinary Research and Industries Collaborations","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129594453","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}
The aim of this research is to discuss the use of Vine Copula with dimension for measuring the dependencies among yield price, crop yield, and standard rainfall index, to calculate the insurance premium. This research is focused at Dlingo, Bantul, where the farmers are depend on rainfall or other water resources. The adoption of standard rainfall index CHS as part of Indemnity decision is reasonable as there are strong correlation between amount of rainfall and yield. In D-Vine structure, the most proper copula to explain the dependence between yield price and the crop yield is Joe copula with θ=1.76 and τ=0.3, while for the crop yield and the standard rainfall index is Frank copula with θ=4.98 and τ=0.46. The simulations data shows that the insurance premium of crop insurance based on rainfall index will give various options of premium rather than traditional crop insurance. The lower value of CHSα will give a lower premium for farmers, however it will impact the decision of indemnity since the indemnity will be paid if CHS t ≤ CHSα. The most important thing for this insurance contract is there are two layers for insurer to claim the policy, one is the CHSt related to CHS α and Ip related to revenue I. In fact, if the value of CHSα is increasing the net single premium will also increase. For similar target income, it can be concluded that the premiums for insurance based on CHS are less expensive compared to traditional crop insurance.
{"title":"Calculation of crop insurance premium based on dependence among yield price, crop yield, and standard rainfall index using vine copula","authors":"A. Hidayat, Gunardi","doi":"10.1063/1.5139122","DOIUrl":"https://doi.org/10.1063/1.5139122","url":null,"abstract":"The aim of this research is to discuss the use of Vine Copula with dimension for measuring the dependencies among yield price, crop yield, and standard rainfall index, to calculate the insurance premium. This research is focused at Dlingo, Bantul, where the farmers are depend on rainfall or other water resources. The adoption of standard rainfall index CHS as part of Indemnity decision is reasonable as there are strong correlation between amount of rainfall and yield. In D-Vine structure, the most proper copula to explain the dependence between yield price and the crop yield is Joe copula with θ=1.76 and τ=0.3, while for the crop yield and the standard rainfall index is Frank copula with θ=4.98 and τ=0.46. The simulations data shows that the insurance premium of crop insurance based on rainfall index will give various options of premium rather than traditional crop insurance. The lower value of CHSα will give a lower premium for farmers, however it will impact the decision of indemnity since the indemnity will be paid if CHS t ≤ CHSα. The most important thing for this insurance contract is there are two layers for insurer to claim the policy, one is the CHSt related to CHS α and Ip related to revenue I. In fact, if the value of CHSα is increasing the net single premium will also increase. For similar target income, it can be concluded that the premiums for insurance based on CHS are less expensive compared to traditional crop insurance.","PeriodicalId":209108,"journal":{"name":"PROCEEDINGS OF THE 8TH SEAMS-UGM INTERNATIONAL CONFERENCE ON MATHEMATICS AND ITS APPLICATIONS 2019: Deepening Mathematical Concepts for Wider Application through Multidisciplinary Research and Industries Collaborations","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129462537","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}
PROCEEDINGS OF THE 8TH SEAMS-UGM INTERNATIONAL CONFERENCE ON MATHEMATICS AND ITS APPLICATIONS 2019: Deepening Mathematical Concepts for Wider Application through Multidisciplinary Research and Industries Collaborations
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