F. A. Sitepu, S. Pambudi, F. Shabihah, C. Ikhsan, B. Yohan, R. Lestari
Chikungunya virus infection (CHIKV) causes symptoms of chikungunya fever and joint pain. The chikungunya virus is spread by the bite of an Aedes mosquito. The symptoms of CHIKV and dengue virus (DENV) infection are similar and are spread by the same vector. Diagnosis of CHIKV infection is carried out by expensive molecular detection and immunological detection (RDT) as an alternative diagnosis. The material to be used for the development of RDT CHIKV is the envelope 2 protein (E2) CHIKV. This study aims to obtain pPICZaA-E2 which is transformed into Escherichia coli TOP10. The pPICZaA plasmid and the E2 CHIKV gene were cloned into E. coli TOP10 and grown onto LB+zeocin agar medium. Cultures grown on the medium were verified for colonies carrying pPICZaA-E2 using PCR colony and restriction. The PCR verification results of the colonies from the growing cultures showed a band measuring 1.260 bp. The results of the restriction verification obtained colonies with two bands measuring 3.569 and 1.260 bp. It was concluded that the E. coli TOP10 colonies carried pPICZaA-E2. Sequencing of the isolated pPICZaA-E2 plasmid is required.
{"title":"Cloning of chikungunya virus envelope 2 (E2) gene to pPICZaA in Escherichia coli TOP10","authors":"F. A. Sitepu, S. Pambudi, F. Shabihah, C. Ikhsan, B. Yohan, R. Lestari","doi":"10.1063/5.0059272","DOIUrl":"https://doi.org/10.1063/5.0059272","url":null,"abstract":"Chikungunya virus infection (CHIKV) causes symptoms of chikungunya fever and joint pain. The chikungunya virus is spread by the bite of an Aedes mosquito. The symptoms of CHIKV and dengue virus (DENV) infection are similar and are spread by the same vector. Diagnosis of CHIKV infection is carried out by expensive molecular detection and immunological detection (RDT) as an alternative diagnosis. The material to be used for the development of RDT CHIKV is the envelope 2 protein (E2) CHIKV. This study aims to obtain pPICZaA-E2 which is transformed into Escherichia coli TOP10. The pPICZaA plasmid and the E2 CHIKV gene were cloned into E. coli TOP10 and grown onto LB+zeocin agar medium. Cultures grown on the medium were verified for colonies carrying pPICZaA-E2 using PCR colony and restriction. The PCR verification results of the colonies from the growing cultures showed a band measuring 1.260 bp. The results of the restriction verification obtained colonies with two bands measuring 3.569 and 1.260 bp. It was concluded that the E. coli TOP10 colonies carried pPICZaA-E2. Sequencing of the isolated pPICZaA-E2 plasmid is required.","PeriodicalId":20561,"journal":{"name":"PROCEEDINGS OF THE 6TH INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES 2020 (ISCPMS 2020)","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87868854","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}
R. Diandarma, D. Lestari, S. Mardiyati, R. A. Kafi, S. Devila, L. Safitri
Modeling the data with a standard distribution is usually difficult to do because of the different characteristics of the body and tail in data. For example, Gamma distribution that has the right-skewing and light tail characteristics is considered unable to model the amount of claim that has a heavy tail. However, the correct fit of the model in the body data and tail data is important in analyzing the risk. Therefore, the splicing distribution is introduced at a threshold value that separates the body and the tail of data. In this paper, splicing distribution at a threshold value is used to model the amount of claim that has heavy tails. The splicing distribution in this paper links a light-tailed distribution for the body data and heavy-tailed distribution for the tail data. In this paper, the splicing distribution of the Truncated Gamma is used to model the data of Phoenix City claim below the threshold value and the Truncated Weibull distribution to model the data above the threshold value. By considering the result of the Kolmogorov-Smirnov test, it can be concluded that this distribution is suitable for modeling Phoenix City claim dataset.
{"title":"Truncated gamma-truncated Weibull distribution for modeling claim severity","authors":"R. Diandarma, D. Lestari, S. Mardiyati, R. A. Kafi, S. Devila, L. Safitri","doi":"10.1063/5.0059259","DOIUrl":"https://doi.org/10.1063/5.0059259","url":null,"abstract":"Modeling the data with a standard distribution is usually difficult to do because of the different characteristics of the body and tail in data. For example, Gamma distribution that has the right-skewing and light tail characteristics is considered unable to model the amount of claim that has a heavy tail. However, the correct fit of the model in the body data and tail data is important in analyzing the risk. Therefore, the splicing distribution is introduced at a threshold value that separates the body and the tail of data. In this paper, splicing distribution at a threshold value is used to model the amount of claim that has heavy tails. The splicing distribution in this paper links a light-tailed distribution for the body data and heavy-tailed distribution for the tail data. In this paper, the splicing distribution of the Truncated Gamma is used to model the data of Phoenix City claim below the threshold value and the Truncated Weibull distribution to model the data above the threshold value. By considering the result of the Kolmogorov-Smirnov test, it can be concluded that this distribution is suitable for modeling Phoenix City claim dataset.","PeriodicalId":20561,"journal":{"name":"PROCEEDINGS OF THE 6TH INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES 2020 (ISCPMS 2020)","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90792622","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}
Silver nanowires (AgNW) is one of the great candidates to replace the role of expensive and relatively rare indium tin oxide (ITO) as the primary material for transparent conducting electrodes (TCEs). TCEs are essential components in numbers of optoelectronic devices, such as organic light-emitting diode (OLED), touchscreen, and solar cells. The specific attribute of TCEs in both optical transmittance and electrical conductivity offers a possible extraction of electrical carriers while transmitting light through the layer. In this study, AgNW was synthesized using a wet chemistry method and deposited on glass substrates with the method of spin coating. In favor to enhance the performance of TCEs, the optimization of number of deposition and post-treatment annealing at 200 °C on glass substrate was then applied. The Hall Effect and UV-Vis Spectroscopy characterization results show that the Figure of Merit (FOM) of AgNW in this study reaches 6.27 × 10−3 Ω−1 that is comparable with FOM of commercial ITO of 7.16 × 10−3 Ω−1. The present results provide a plausible way to design and fabricate a new alternative material for TCEs with relatively low cost.
{"title":"Effect of deposition repetition and annealing treatment on the figure of merit of silver nanowire–based transparent conducting electrodes","authors":"A. R. Fareza, L. Roza, V. Fauzia","doi":"10.1063/5.0058896","DOIUrl":"https://doi.org/10.1063/5.0058896","url":null,"abstract":"Silver nanowires (AgNW) is one of the great candidates to replace the role of expensive and relatively rare indium tin oxide (ITO) as the primary material for transparent conducting electrodes (TCEs). TCEs are essential components in numbers of optoelectronic devices, such as organic light-emitting diode (OLED), touchscreen, and solar cells. The specific attribute of TCEs in both optical transmittance and electrical conductivity offers a possible extraction of electrical carriers while transmitting light through the layer. In this study, AgNW was synthesized using a wet chemistry method and deposited on glass substrates with the method of spin coating. In favor to enhance the performance of TCEs, the optimization of number of deposition and post-treatment annealing at 200 °C on glass substrate was then applied. The Hall Effect and UV-Vis Spectroscopy characterization results show that the Figure of Merit (FOM) of AgNW in this study reaches 6.27 × 10−3 Ω−1 that is comparable with FOM of commercial ITO of 7.16 × 10−3 Ω−1. The present results provide a plausible way to design and fabricate a new alternative material for TCEs with relatively low cost.","PeriodicalId":20561,"journal":{"name":"PROCEEDINGS OF THE 6TH INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES 2020 (ISCPMS 2020)","volume":"67 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84041199","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}
Zirconium alloys are the materials of choice for nuclear fuel cladding due to low thermal neutron absorption, with excellent thermal and mechanical properties. As part of defence in depth concept, zirconium-based cladding shall be able to maintain its integrity and prevent the release of fission products to the reactor core. In particular, chemical degradation, due to corrosion, hydriding and pellet-cladding interaction, can compromise the fundamental safety functions of fuel cladding. Due to the risks of such chemical degradation of zirconium alloys, various countries undertake divergent regulatory approaches to ensure the integrity of fuel cladding. This research paper is the first attempt to review these regulatory approaches and to provide a technical basis for future regulation development for the safety of nuclear power plants. This research comprises of literature review of various factors that cause fuel failures in the operation of light water reactors as well as the prevalent international safety standards and regulations developed by several countries. Corrosion can cause oxide layer build-up that reduce heat transfer during accident condition. Excessive hydrogen uptake can cause embrittlement during loss-of-coolant accident. Pellet-cladding interaction causes fuel failure during normal operation of nuclear reactors. The research on chemical degradation of zirconium cladding remains intensive that continues to enhance the protection of fuel cladding. Based on the available knowledge in nuclear research community, the International Atomic Energy Agency (IAEA) has established international standards to ensure the highest reliability of fuel cladding, from operation to accident conditions. Regulatory bodies around the world aspire to adopt these internationally agreed standards. However, they also implement the national codes and standards in addition to these international standards that are relevant to their existing nuclear fleet. There is no unique regulatory approach in ensuring the integrity of fuel claddings from chemical degradation, but all reflect the strong commitment of the international community to the highest level of nuclear safety. Bapeten and other regulatory bodies need to review such varying regulatory approaches and adopt the most sensible and reliable regulatory regimes that are relevant to their domestic needs, circumstances, and capabilities.
{"title":"Regulatory approaches in mitigating chemical degradation of zirconium alloys in the design and operation of light water reactors","authors":"P. Wiringgalih, Y. Pramono","doi":"10.1063/5.0060923","DOIUrl":"https://doi.org/10.1063/5.0060923","url":null,"abstract":"Zirconium alloys are the materials of choice for nuclear fuel cladding due to low thermal neutron absorption, with excellent thermal and mechanical properties. As part of defence in depth concept, zirconium-based cladding shall be able to maintain its integrity and prevent the release of fission products to the reactor core. In particular, chemical degradation, due to corrosion, hydriding and pellet-cladding interaction, can compromise the fundamental safety functions of fuel cladding. Due to the risks of such chemical degradation of zirconium alloys, various countries undertake divergent regulatory approaches to ensure the integrity of fuel cladding. This research paper is the first attempt to review these regulatory approaches and to provide a technical basis for future regulation development for the safety of nuclear power plants. This research comprises of literature review of various factors that cause fuel failures in the operation of light water reactors as well as the prevalent international safety standards and regulations developed by several countries. Corrosion can cause oxide layer build-up that reduce heat transfer during accident condition. Excessive hydrogen uptake can cause embrittlement during loss-of-coolant accident. Pellet-cladding interaction causes fuel failure during normal operation of nuclear reactors. The research on chemical degradation of zirconium cladding remains intensive that continues to enhance the protection of fuel cladding. Based on the available knowledge in nuclear research community, the International Atomic Energy Agency (IAEA) has established international standards to ensure the highest reliability of fuel cladding, from operation to accident conditions. Regulatory bodies around the world aspire to adopt these internationally agreed standards. However, they also implement the national codes and standards in addition to these international standards that are relevant to their existing nuclear fleet. There is no unique regulatory approach in ensuring the integrity of fuel claddings from chemical degradation, but all reflect the strong commitment of the international community to the highest level of nuclear safety. Bapeten and other regulatory bodies need to review such varying regulatory approaches and adopt the most sensible and reliable regulatory regimes that are relevant to their domestic needs, circumstances, and capabilities.","PeriodicalId":20561,"journal":{"name":"PROCEEDINGS OF THE 6TH INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES 2020 (ISCPMS 2020)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80659440","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}
Quantile regression is a regression method that modelling a relationship between quantile of variable response and one or more variable predictors. Quantile regression has advantages that linear regression does not have; it is robust against outliers and can model heteroscedasticity data. The parameters of quantile regression can be estimated using the Bayesian method. The Bayesian method is a data analysis tool derived based on the Bayesian inference principle. Bayesian inference is the process of studying data analysis inductively with the Bayes theorem. To estimate regression parameters with Bayesian inference, it is necessary to find the posterior distribution of the regression parameters where the posterior distribution is proportional to the product of the prior distribution and its likelihood function. Since the calculation of the posterior distribution analytically is difficult to do if more parameters are estimated, the Markov Chain Monte Carlo (MCMC) method is proposed. The use of the Bayesian method in quantile regression has advantages, namely the use of MCMC has the advantages of obtaining sample parameter values from an unknown posterior distribution, using computationally efficient, and easy to implement. Yu and Moyeed (2001) introduced Bayesian quantile regression using the likelihood function of errors with an Asymmetric Laplace Distribution (ALD) and found that minimizing parameter estimates in quantile regression is the same as maximizing the likelihood function of errors with an Asymmetric Laplace Distribution (ALD). The method used to estimate quantile regression parameters is Gibbs sampling from the ALD, which is a combination of the exponential and normal distributions. To find the parameters of the regression model by sampling the posterior distribution found in this thesis. The results obtained from Gibbs sampling are a sample sequence of estimated parameters. After obtaining the sample sequences, the sample lines are averaged to obtain an estimated regression parameter. The case study in this thesis discusses the effect of risk factors from motor vehicle insurance customers on the size of claims submitted by customers.
{"title":"Parameter estimation of Bayesian quantile regression","authors":"D. Dichandra, I. Fithriani, S. Nurrohmah","doi":"10.1063/5.0059103","DOIUrl":"https://doi.org/10.1063/5.0059103","url":null,"abstract":"Quantile regression is a regression method that modelling a relationship between quantile of variable response and one or more variable predictors. Quantile regression has advantages that linear regression does not have; it is robust against outliers and can model heteroscedasticity data. The parameters of quantile regression can be estimated using the Bayesian method. The Bayesian method is a data analysis tool derived based on the Bayesian inference principle. Bayesian inference is the process of studying data analysis inductively with the Bayes theorem. To estimate regression parameters with Bayesian inference, it is necessary to find the posterior distribution of the regression parameters where the posterior distribution is proportional to the product of the prior distribution and its likelihood function. Since the calculation of the posterior distribution analytically is difficult to do if more parameters are estimated, the Markov Chain Monte Carlo (MCMC) method is proposed. The use of the Bayesian method in quantile regression has advantages, namely the use of MCMC has the advantages of obtaining sample parameter values from an unknown posterior distribution, using computationally efficient, and easy to implement. Yu and Moyeed (2001) introduced Bayesian quantile regression using the likelihood function of errors with an Asymmetric Laplace Distribution (ALD) and found that minimizing parameter estimates in quantile regression is the same as maximizing the likelihood function of errors with an Asymmetric Laplace Distribution (ALD). The method used to estimate quantile regression parameters is Gibbs sampling from the ALD, which is a combination of the exponential and normal distributions. To find the parameters of the regression model by sampling the posterior distribution found in this thesis. The results obtained from Gibbs sampling are a sample sequence of estimated parameters. After obtaining the sample sequences, the sample lines are averaged to obtain an estimated regression parameter. The case study in this thesis discusses the effect of risk factors from motor vehicle insurance customers on the size of claims submitted by customers.","PeriodicalId":20561,"journal":{"name":"PROCEEDINGS OF THE 6TH INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES 2020 (ISCPMS 2020)","volume":"34 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81312033","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 most commonly used time series model is the discrete time series which assumes the variables being tested are continuous and produce continuous values. Whereas in many applications, a discrete time series model is needed to handle discrete variables and produce discrete values as well. The time series model that handles count or non-negative integer data is the Integer-valued Autoregressive model with the pth-order or INAR(p). This model is built with binomial thinning operator which implements probabilistic operations with discrete distribution that are suitable to model count data such as Poisson and Binomial. Model parameters will be estimated using the Yule-Walker method. In this research, we will discuss and describe the characteristics of the INAR(p) model using the binomial thinning operator. The INAR(p) specification follows the Autoregressive model with the pth order, AR(p). Forecasting in INAR(p) uses median forecasting by calculating the conditional probability of each possible non-negative integer value, then selecting a forecast value with a cumulative conditional probability greater than 0.5. The INAR(p) time series model will be applied to the 115 simulated data with non-negative integer values.
{"title":"Integer-valued Pth-order autoregressive model","authors":"M. Novita, B. Belinda","doi":"10.1063/5.0059291","DOIUrl":"https://doi.org/10.1063/5.0059291","url":null,"abstract":"The most commonly used time series model is the discrete time series which assumes the variables being tested are continuous and produce continuous values. Whereas in many applications, a discrete time series model is needed to handle discrete variables and produce discrete values as well. The time series model that handles count or non-negative integer data is the Integer-valued Autoregressive model with the pth-order or INAR(p). This model is built with binomial thinning operator which implements probabilistic operations with discrete distribution that are suitable to model count data such as Poisson and Binomial. Model parameters will be estimated using the Yule-Walker method. In this research, we will discuss and describe the characteristics of the INAR(p) model using the binomial thinning operator. The INAR(p) specification follows the Autoregressive model with the pth order, AR(p). Forecasting in INAR(p) uses median forecasting by calculating the conditional probability of each possible non-negative integer value, then selecting a forecast value with a cumulative conditional probability greater than 0.5. The INAR(p) time series model will be applied to the 115 simulated data with non-negative integer values.","PeriodicalId":20561,"journal":{"name":"PROCEEDINGS OF THE 6TH INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES 2020 (ISCPMS 2020)","volume":"34 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91299367","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 objective of this research is to study the influence of the substitution of Zn on Fe-site to the dielectric properties of LaFeO3. A series of LaFe1-xZnxO3 perovskite materials (x = 0.03 and 0.05) were successfully synthesized by the sol-gel method and then sintered to form bulk samples. XRD, SEM, and EDAX characterized the structure and element composition. The RLC-Meter used to measure electrical properties as well as resistance, dielectric constant, and tan loss. All compounds were single-phase, with no impurity phase. X-ray diffraction analysis showed that all samples have orthorhombic crystal structure and Pbnm space group. The SEM results of the bulk samples showed that the morphology of the particles was uniformly distributed. The electrical properties of LaFe1-xZnxO3 (x = 0.03 and 0.05) in the frequency range of 0.1 kHz-1000 kHz at room temperature were determined by impedance spectroscopy. Zn-doped LaFeO3 leads to an increase in the semicircular diameter Nyquist plot, impedance value, dielectric loss, and material conductivity. These results prove that zinc doping enhances the electrical properties of the material.
{"title":"Effect of zinc doping on the electrical properties of LaFeO3 perovskite","authors":"R. Regiana, D. Triyono, F. Fajriyani","doi":"10.1063/5.0058838","DOIUrl":"https://doi.org/10.1063/5.0058838","url":null,"abstract":"The objective of this research is to study the influence of the substitution of Zn on Fe-site to the dielectric properties of LaFeO3. A series of LaFe1-xZnxO3 perovskite materials (x = 0.03 and 0.05) were successfully synthesized by the sol-gel method and then sintered to form bulk samples. XRD, SEM, and EDAX characterized the structure and element composition. The RLC-Meter used to measure electrical properties as well as resistance, dielectric constant, and tan loss. All compounds were single-phase, with no impurity phase. X-ray diffraction analysis showed that all samples have orthorhombic crystal structure and Pbnm space group. The SEM results of the bulk samples showed that the morphology of the particles was uniformly distributed. The electrical properties of LaFe1-xZnxO3 (x = 0.03 and 0.05) in the frequency range of 0.1 kHz-1000 kHz at room temperature were determined by impedance spectroscopy. Zn-doped LaFeO3 leads to an increase in the semicircular diameter Nyquist plot, impedance value, dielectric loss, and material conductivity. These results prove that zinc doping enhances the electrical properties of the material.","PeriodicalId":20561,"journal":{"name":"PROCEEDINGS OF THE 6TH INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES 2020 (ISCPMS 2020)","volume":"82 11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88037310","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}
A. IvandiniTribidasari, G. ChurchillDavid, LeeYoungil, A. Binti, MargulesChris
{"title":"Advisory and Editorial Board: 6th International Symposium on Current Progress in Mathematics and Sciences (ISCPMS 2020)","authors":"A. IvandiniTribidasari, G. ChurchillDavid, LeeYoungil, A. Binti, MargulesChris","doi":"10.1063/12.0005615","DOIUrl":"https://doi.org/10.1063/12.0005615","url":null,"abstract":"","PeriodicalId":20561,"journal":{"name":"PROCEEDINGS OF THE 6TH INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES 2020 (ISCPMS 2020)","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86903837","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}
D. G. W. K. D. Rasanji, A. Z. Pamungkas, R. Wibowo, Y. Krisnandi
Sawdust of Oil Palm Empty Fruit Bunches (OPEFB/TKKS (Tandan Kosong Kelapa Sawit)) as a waste product from oil palm plants could be used as mesoporous carbon which was used as an adsorbent for Cu2+ and Cd2+ metal ions because it was a lignocellulose compound which had a hydroxyl (OH) functional group that could bind metals. This adsorption ability could be increased by delignification and sulfonated treatment of OPEFB (TKKS) sawdust. The treatment shown that activated OPEFB carbon can achieve maximum adsorption that is close to activated carbon.
{"title":"Synthesis of mesoporous carbon from sulfonated modified crude palm oil as adsorbents of heavy metal Cu2+ and Cd2+","authors":"D. G. W. K. D. Rasanji, A. Z. Pamungkas, R. Wibowo, Y. Krisnandi","doi":"10.1063/5.0058960","DOIUrl":"https://doi.org/10.1063/5.0058960","url":null,"abstract":"Sawdust of Oil Palm Empty Fruit Bunches (OPEFB/TKKS (Tandan Kosong Kelapa Sawit)) as a waste product from oil palm plants could be used as mesoporous carbon which was used as an adsorbent for Cu2+ and Cd2+ metal ions because it was a lignocellulose compound which had a hydroxyl (OH) functional group that could bind metals. This adsorption ability could be increased by delignification and sulfonated treatment of OPEFB (TKKS) sawdust. The treatment shown that activated OPEFB carbon can achieve maximum adsorption that is close to activated carbon.","PeriodicalId":20561,"journal":{"name":"PROCEEDINGS OF THE 6TH INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES 2020 (ISCPMS 2020)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89576945","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 few goals of statistical modeling is to see and analyze the probability of an event which can be represented with data. A probability distribution that is used for modeling data should have some abilities such as flexibility for modeling different kinds of data. Therefore, modeling data is of great importance. Furthermore, insurance companies also need to model data, which in this case is called modeling claim data. Modeling the claims distribution has its own challenge (e.g. skewed and heavy tailed) since most of the claim distributions are different from any classical distributions, therefore researchers are trying to find new models that can fit insurance data better. In this paper, a composite Exponential-Pareto distribution was proposed and introduced. This distribution is equal, but not equivalent to, an exponential density up to a certain threshold value, and a Pareto type-I density for the rest of the model. When being compared with the exponential distribution, the emerging density has a similar shape and a larger tail, and while being compared with the Pareto distribution, the emerging density has a smaller tail. A method to develop a composite distribution is called as composite parametric modeling, which introduced by Cooray and Ananda (2005). In this model, both the exponential distribution and the Pareto type-I distribution have the same weight. Based on the result, composite Exponential-Pareto distribution has some limitations, which are likely to severely diminish its potential for practical applications to real world insurance data. In order to address these issues, there are two different composite Exponential-Pareto distributions based on exponential and Pareto type-I distributions in order to address these concerns. These two different composite Exponential-Pareto distributions are based on the two-component mixture model introduced by Scollnik (2007). The first distribution, which is a reinterpreted composite Exponential-Pareto distribution from the first composite Exponential-Pareto distribution based on the two-component mixture model, has a fixed mixing weight. Meanwhile, the second distribution is a composite Exponential-Pareto distribution with a mixing weight that is not fixed so the distribution can be more flexible and can model different kinds of data. These three composite Exponential-Pareto distributions has k-th raw-moment that only defined for some k > 0. Therefore, this distribution can be categorized as a heavy-tail distribution. The result of this research is a composite distribution that could model a lot of data with characteristics such as unimodal, right-skewed, and heavy-tail because the composite distribution has similar characteristics. A data illustration was presented as a demonstration for how to implement the composite Exponential-Pareto distribution.
{"title":"Composite Exponential-Pareto distribution","authors":"B. N. Pratama, S. Nurrohmah, I. Fithriani","doi":"10.1063/5.0059049","DOIUrl":"https://doi.org/10.1063/5.0059049","url":null,"abstract":"One of the few goals of statistical modeling is to see and analyze the probability of an event which can be represented with data. A probability distribution that is used for modeling data should have some abilities such as flexibility for modeling different kinds of data. Therefore, modeling data is of great importance. Furthermore, insurance companies also need to model data, which in this case is called modeling claim data. Modeling the claims distribution has its own challenge (e.g. skewed and heavy tailed) since most of the claim distributions are different from any classical distributions, therefore researchers are trying to find new models that can fit insurance data better. In this paper, a composite Exponential-Pareto distribution was proposed and introduced. This distribution is equal, but not equivalent to, an exponential density up to a certain threshold value, and a Pareto type-I density for the rest of the model. When being compared with the exponential distribution, the emerging density has a similar shape and a larger tail, and while being compared with the Pareto distribution, the emerging density has a smaller tail. A method to develop a composite distribution is called as composite parametric modeling, which introduced by Cooray and Ananda (2005). In this model, both the exponential distribution and the Pareto type-I distribution have the same weight. Based on the result, composite Exponential-Pareto distribution has some limitations, which are likely to severely diminish its potential for practical applications to real world insurance data. In order to address these issues, there are two different composite Exponential-Pareto distributions based on exponential and Pareto type-I distributions in order to address these concerns. These two different composite Exponential-Pareto distributions are based on the two-component mixture model introduced by Scollnik (2007). The first distribution, which is a reinterpreted composite Exponential-Pareto distribution from the first composite Exponential-Pareto distribution based on the two-component mixture model, has a fixed mixing weight. Meanwhile, the second distribution is a composite Exponential-Pareto distribution with a mixing weight that is not fixed so the distribution can be more flexible and can model different kinds of data. These three composite Exponential-Pareto distributions has k-th raw-moment that only defined for some k > 0. Therefore, this distribution can be categorized as a heavy-tail distribution. The result of this research is a composite distribution that could model a lot of data with characteristics such as unimodal, right-skewed, and heavy-tail because the composite distribution has similar characteristics. A data illustration was presented as a demonstration for how to implement the composite Exponential-Pareto distribution.","PeriodicalId":20561,"journal":{"name":"PROCEEDINGS OF THE 6TH INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES 2020 (ISCPMS 2020)","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78763043","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}
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