Nikken Halim, Marwah Hotimah Nada Putri, Irfaliani Alviari, Fadillah Luthfiyah, Hera Septiani, B. D. A. Prayanti
Malaria is an infectious disease caused by plasmodium through the bite of the Anopheles sp mosquito. female (Roach, 2012). Malaria disease which hit the Bangka Belitung Islands Province in 2005 experienced a spike, reaching 36,901 people out of 981,573 residents and claimed the lives of 12 local residents. In 2011, the Bangka Belitung Islands Province was declared an endemic area for malaria. This research aims to model and interpret the spread of malaria using the SEIR model and predict the spread of malaria using parameter estimates. The steps in analyzing the SEIR model on the spread of malaria are making assumptions, forming a SEIR model, determining the equilibrium point and analyzing the stability of the equilibrium point, determining the basic reproduction number, and carrying out a simulation of the SEIR model that has been obtained. The SEIR model is classified into 4 classes, namely Susceptible (susceptible individuals), Exposed (individuals who have symptoms), Infected (infected individuals), and Recovered (recovered individuals). The data used in this research is data on the number of Susceptible, Exposed, Infected and Recovered malaria cases in 2022 obtained from the Bangka Belitung Islands Provincial Health Service. The SEIR mathematical model is used to calculate the equilibrium point and basic reproduction number. Based on the SEIR model simulation results, it was found that the susceptible population decreased from the 0th month to the 48th month. As for the exposed population, there were 9,623 people in month 0, but in this condition the population decreased drastically per month. Furthermore, for the infected population there were 129 people in month 0, but in this condition the number of infected decreased drastically per month along with the decrease in the exposed population. For individuals who recovered, there was a decrease from the 0th month to the 48th month.
{"title":"Modeling of the Spread of Malaria in the Bangka Belitung Islands Province Using the SEIR Method","authors":"Nikken Halim, Marwah Hotimah Nada Putri, Irfaliani Alviari, Fadillah Luthfiyah, Hera Septiani, B. D. A. Prayanti","doi":"10.29303/emj.v7i1.189","DOIUrl":"https://doi.org/10.29303/emj.v7i1.189","url":null,"abstract":"Malaria is an infectious disease caused by plasmodium through the bite of the Anopheles sp mosquito. female (Roach, 2012). Malaria disease which hit the Bangka Belitung Islands Province in 2005 experienced a spike, reaching 36,901 people out of 981,573 residents and claimed the lives of 12 local residents. In 2011, the Bangka Belitung Islands Province was declared an endemic area for malaria. This research aims to model and interpret the spread of malaria using the SEIR model and predict the spread of malaria using parameter estimates. The steps in analyzing the SEIR model on the spread of malaria are making assumptions, forming a SEIR model, determining the equilibrium point and analyzing the stability of the equilibrium point, determining the basic reproduction number, and carrying out a simulation of the SEIR model that has been obtained. The SEIR model is classified into 4 classes, namely Susceptible (susceptible individuals), Exposed (individuals who have symptoms), Infected (infected individuals), and Recovered (recovered individuals). The data used in this research is data on the number of Susceptible, Exposed, Infected and Recovered malaria cases in 2022 obtained from the Bangka Belitung Islands Provincial Health Service. The SEIR mathematical model is used to calculate the equilibrium point and basic reproduction number. Based on the SEIR model simulation results, it was found that the susceptible population decreased from the 0th month to the 48th month. As for the exposed population, there were 9,623 people in month 0, but in this condition the population decreased drastically per month. Furthermore, for the infected population there were 129 people in month 0, but in this condition the number of infected decreased drastically per month along with the decrease in the exposed population. For individuals who recovered, there was a decrease from the 0th month to the 48th month.","PeriodicalId":281429,"journal":{"name":"EIGEN MATHEMATICS JOURNAL","volume":"56 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140736625","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}
Kami mempelajari model predator-prey dengan perilaku anti-predator dan efek Allee pada prey. Efek Allee merupakan fenomena ekologi yang menggambarkan penurunan pertumbuhan populasi karena berkurangnya kepadatan suatu populasi spesies, sedangkan perilaku anti predator adalah perilaku prey untuk melindungi diri dari predator. Kami menemukan 4 titik kesetimbangan, yaitu titik kepunahan kedua spesies , dua titik kepunahan predator dan ) dan satu titik koeksistensi kedua spesies . Kestabilan dan tergantung dari parameter yang diberikan, sedangkan titik selalu tidak stabil. Selanjutnya kami melakukan simulasi numerik dengan metode Runge-Kutta menggunakan bahasa pemrograman Python untuk mengkonfirmasi analisis model secara grafis.
{"title":"Analisis Dinamik Model Predator-prey dengan Perilaku Anti Predator serta Efek Allee pada Prey","authors":"Hady Rasikhun, M. D. Putra, Rizka Rizqi Robbi","doi":"10.29303/emj.v6i2.191","DOIUrl":"https://doi.org/10.29303/emj.v6i2.191","url":null,"abstract":"Kami mempelajari model predator-prey dengan perilaku anti-predator dan efek Allee pada prey. Efek Allee merupakan fenomena ekologi yang menggambarkan penurunan pertumbuhan populasi karena berkurangnya kepadatan suatu populasi spesies, sedangkan perilaku anti predator adalah perilaku prey untuk melindungi diri dari predator. Kami menemukan 4 titik kesetimbangan, yaitu titik kepunahan kedua spesies , dua titik kepunahan predator dan ) dan satu titik koeksistensi kedua spesies . Kestabilan dan tergantung dari parameter yang diberikan, sedangkan titik selalu tidak stabil. Selanjutnya kami melakukan simulasi numerik dengan metode Runge-Kutta menggunakan bahasa pemrograman Python untuk mengkonfirmasi analisis model secara grafis.","PeriodicalId":281429,"journal":{"name":"EIGEN MATHEMATICS JOURNAL","volume":"11 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139531468","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}
Student study time is the time needed by students to complete their education, which starts from the time they enter college until they are declared graduated or have completed their study period. In the study period data, survival time observations were only carried out partially or not until the failure event. In other words, termination occurs until the observation deadline. This termination occurred due to several factors that allegedly influenced the student's study period. Using study period data for students of the Faculty of Engineering, University of Bangka Belitung, class of 2015/2016, this study used the Kaplan Meier Estimation to see the survival function of each factor causing the length of study period graphically and the Log Rank Test statistically. Meanwhile, to look at the factors that determine the length of a student's study period, researchers used the Cox Regression and Maximum Likelihood Estimation (MLE) models to find the best model. The results of the data analysis show that there are differences in the survival function in each category for all variables graphically, while the statistical comparison of the results of the estimation of the survival function curve based on gender and organizational status is not significantly different. The results of the analysis also show that the proportional hazard assumption is fulfilled through the cumulative hazard log so that categorical variables can be used in the Cox Regression model. Based on the results of the likelihood estimation, the variables that have a significant effect on the study period of Engineering Faculty students are majors and GPA variables. Furthermore, from the interpretation of the model parameters, it is obtained that the Hazard Ratio (HR) value for the study period of Mechanical, Mining and Electrical Engineering students is faster than that of Civil Engineering students, while students with GPA ≥ 3.00 have a shorter study period than students with GPA < 3.00.
{"title":"Model Regresi Cox Untuk Data Masa Studi (Studi Kasus: Data Masa Studi Mahasiswa Fakultas Teknik Universitas Bangka Belitung)","authors":"Ineu Sulistiana, Elyas Kustiawan, Ririn Amelia","doi":"10.29303/emj.v6i2.170","DOIUrl":"https://doi.org/10.29303/emj.v6i2.170","url":null,"abstract":"Student study time is the time needed by students to complete their education, which starts from the time they enter college until they are declared graduated or have completed their study period. In the study period data, survival time observations were only carried out partially or not until the failure event. In other words, termination occurs until the observation deadline. This termination occurred due to several factors that allegedly influenced the student's study period. Using study period data for students of the Faculty of Engineering, University of Bangka Belitung, class of 2015/2016, this study used the Kaplan Meier Estimation to see the survival function of each factor causing the length of study period graphically and the Log Rank Test statistically. Meanwhile, to look at the factors that determine the length of a student's study period, researchers used the Cox Regression and Maximum Likelihood Estimation (MLE) models to find the best model. The results of the data analysis show that there are differences in the survival function in each category for all variables graphically, while the statistical comparison of the results of the estimation of the survival function curve based on gender and organizational status is not significantly different. The results of the analysis also show that the proportional hazard assumption is fulfilled through the cumulative hazard log so that categorical variables can be used in the Cox Regression model. Based on the results of the likelihood estimation, the variables that have a significant effect on the study period of Engineering Faculty students are majors and GPA variables. Furthermore, from the interpretation of the model parameters, it is obtained that the Hazard Ratio (HR) value for the study period of Mechanical, Mining and Electrical Engineering students is faster than that of Civil Engineering students, while students with GPA ≥ 3.00 have a shorter study period than students with GPA < 3.00.","PeriodicalId":281429,"journal":{"name":"EIGEN MATHEMATICS JOURNAL","volume":"117 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139135475","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}
Siti Dwi Khairun Rahmatin Usman, M. Hadijati, Nurul Fitriyani
Malaria is one of the health problems in West Lombok Regency. There are 413 positive malaria cases, so it is necessary to research the models and factors affecting malaria sufferers' recovery. The analysis used is survival analysis using the Cox Proportional Hazard Regression method. The data used in this study is in the form of secondary data obtained from medical record data from all patients with malaria disease in West Lombok Regency from 2019 to 2020, with dependent variables in the form of recovery time of malaria patients and nine independent variables that are suspected of affecting the recovery of malaria sufferers. This study aims to determine a recovery model for malaria sufferers based on Cox regression and determine the factors that influence the recovery of malaria sufferers in West Lombok Regency. Based on the survival analysis results with the Cox Proportional hazard Regression method, the best model was obtained with two significant variables affecting the recovery time of malaria patients: the parasite type variable and the incidence of pregnancy or not getting pregnant. The model can be interpreted based on hazard ratio values that the variable type of parasite category Plasmodium vivax has a probability of being able to recover within one month of treatment by 2,542 times faster than Plasmodium falciparum. In comparison, the type of parasite in the Plasmodium mix category has a probability of being able to recover within one month of treatment 1.108 times faster than Plasmodium vivax, and for the pregnant or non-pregnant variables for the category of pregnant patients had a 2,307 times faster probability of recovery within one month of treatment compared to non-pregnant patients.
{"title":"Modelling the Recovery of Malaria Patients in West Lombok District Using Cox Regression","authors":"Siti Dwi Khairun Rahmatin Usman, M. Hadijati, Nurul Fitriyani","doi":"10.29303/emj.v6i2.173","DOIUrl":"https://doi.org/10.29303/emj.v6i2.173","url":null,"abstract":"Malaria is one of the health problems in West Lombok Regency. There are 413 positive malaria cases, so it is necessary to research the models and factors affecting malaria sufferers' recovery. The analysis used is survival analysis using the Cox Proportional Hazard Regression method. The data used in this study is in the form of secondary data obtained from medical record data from all patients with malaria disease in West Lombok Regency from 2019 to 2020, with dependent variables in the form of recovery time of malaria patients and nine independent variables that are suspected of affecting the recovery of malaria sufferers. This study aims to determine a recovery model for malaria sufferers based on Cox regression and determine the factors that influence the recovery of malaria sufferers in West Lombok Regency. Based on the survival analysis results with the Cox Proportional hazard Regression method, the best model was obtained with two significant variables affecting the recovery time of malaria patients: the parasite type variable and the incidence of pregnancy or not getting pregnant. The model can be interpreted based on hazard ratio values that the variable type of parasite category Plasmodium vivax has a probability of being able to recover within one month of treatment by 2,542 times faster than Plasmodium falciparum. In comparison, the type of parasite in the Plasmodium mix category has a probability of being able to recover within one month of treatment 1.108 times faster than Plasmodium vivax, and for the pregnant or non-pregnant variables for the category of pregnant patients had a 2,307 times faster probability of recovery within one month of treatment compared to non-pregnant patients.","PeriodicalId":281429,"journal":{"name":"EIGEN MATHEMATICS JOURNAL","volume":"119 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139134306","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}
Clean water is the main and basic need for humans which is of concern to the government. Distribution network system is a very important part to delivering water to all consumers. The lack of water discharge distribution in several areas, especially at the end of the pipeline service, is cause by not optimal water distribution, the flow rate of sorce and leak in pipeline effect. This research has to analyze the optimal network model and determine the maximum flow rate from the PDAM pipeline using modified Edmonds Karp algorithm. Modified Edmonds Karp algorithm is a method for calculating maximum flow of a network. Based on analysis of modified Edmonds Karp algorithm there is a less efficient us of pipe in PDAM network and result of maximum flow from the network is 202,30 liter/second. This means it can be adding flow discharge to the water distribution pipe by PDAM for expedite the flow to consumer with the addition of flow should not exceed 202,30 liter/second.
{"title":"Modifikasi Algoritma Edmonds Karp untuk Menentukan Aliran Maksimum Pada Jaringan Distribusi Air PDAM (Studi Kasus Jaringan Telaga Sari PDAM Giri Menang Mataram)","authors":"Husnul Hotimah, syamsul bahri, Lailia Awalushaumi","doi":"10.29303/emj.v6i2.134","DOIUrl":"https://doi.org/10.29303/emj.v6i2.134","url":null,"abstract":"Clean water is the main and basic need for humans which is of concern to the government. Distribution network system is a very important part to delivering water to all consumers. The lack of water discharge distribution in several areas, especially at the end of the pipeline service, is cause by not optimal water distribution, the flow rate of sorce and leak in pipeline effect. This research has to analyze the optimal network model and determine the maximum flow rate from the PDAM pipeline using modified Edmonds Karp algorithm. Modified Edmonds Karp algorithm is a method for calculating maximum flow of a network. Based on analysis of modified Edmonds Karp algorithm there is a less efficient us of pipe in PDAM network and result of maximum flow from the network is 202,30 liter/second. This means it can be adding flow discharge to the water distribution pipe by PDAM for expedite the flow to consumer with the addition of flow should not exceed 202,30 liter/second.","PeriodicalId":281429,"journal":{"name":"EIGEN MATHEMATICS JOURNAL","volume":"36 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139132373","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}
Rio Satriyantara, Dara Puspita Anggraeni, Irma Risvana Dewi, Alfian Eka Utama
In this work, a discretization process of a fractional-order prey and predator model is discussed. The aim of this work is to describe the population phenomenon which contains prey and predator. In this research, the prey and predator model by Ghosh et al. (2017) is used. The model has an unique form because it contains prey refuge and additional food to predator. In order to give more details on prey and predator population, the model then modified into fractional order and then discretized. The discretization model has three points of equilibrium and one of them named co-existing point of equilibrium. The numerical simulation is used to perform the stability. The numerical simulation is controlled by using mathematical programming language. It resulted that the co-existing point of equilibrium tends to be stable or converge if a small value of (time step) is selected. Otherwise, if a larger value of is selected, then oscillatory is appeared which means the point of equilibrium become unstable or diverge.
本文讨论了分数阶捕食者和猎物模型的离散化过程。这项工作的目的是描述包含猎物和捕食者的种群现象。本研究使用Ghosh et al.(2017)的猎物和捕食者模型。该模型具有独特的形式，因为它包含了猎物的避难所和捕食者的额外食物。为了得到更多关于猎物和捕食者种群的细节，将模型修正为分数阶，然后离散化。离散化模型有三个平衡点，其中一个称为共存平衡点。通过数值模拟对其稳定性进行了验证。采用数学编程语言控制数值模拟。结果表明，如果选取较小的(时间步长)，则共存平衡点趋于稳定或收敛。否则，如果选择较大的值，则出现振荡，即平衡点变得不稳定或发散。
{"title":"Co-Existing Point of Equilibrium in Discretization of Fractional-Order Prey and Predator Model","authors":"Rio Satriyantara, Dara Puspita Anggraeni, Irma Risvana Dewi, Alfian Eka Utama","doi":"10.29303/emj.v6i1.169","DOIUrl":"https://doi.org/10.29303/emj.v6i1.169","url":null,"abstract":"In this work, a discretization process of a fractional-order prey and predator model is discussed. The aim of this work is to describe the population phenomenon which contains prey and predator. In this research, the prey and predator model by Ghosh et al. (2017) is used. The model has an unique form because it contains prey refuge and additional food to predator. In order to give more details on prey and predator population, the model then modified into fractional order and then discretized. The discretization model has three points of equilibrium and one of them named co-existing point of equilibrium. The numerical simulation is used to perform the stability. The numerical simulation is controlled by using mathematical programming language. It resulted that the co-existing point of equilibrium tends to be stable or converge if a small value of (time step) is selected. Otherwise, if a larger value of is selected, then oscillatory is appeared which means the point of equilibrium become unstable or diverge.","PeriodicalId":281429,"journal":{"name":"EIGEN MATHEMATICS JOURNAL","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115888223","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}
Clean water is essential for humans which must be fulfilled for humans survival. The population in Jonggat, Central Lombok, increases from year to year which causes the using of clean water get an increase too. The necessity of rising clean water is not in line with the availability of water in nature, therefore the PDAM (Regency Municipality Waterworks) manages existing water resource. Then, it will be distributed to consumers. The purpose of this research is to determine the optimal solution in the distribution of clean water in Jonggat using Ford Fulkerson algorithm and Dinic algorithm. Both Ford Fulkerson algorithm and Dinic algorithm are methods used to calculate the maximum flow in a network. Based on the results of research using Python software on the Ford Fulkerson algorithm, the maximum current is 133 liters/second, while using the Dinic algorithm, the maximum current is 133.49 liters/second. Meanwhile, the average water flow is delivered by PDAM is 95 liters/second. It means, it can be added the amount of flow in the clean water distribution pipe by the PDAM. It’s for facilitating the flow of water that reaches consumers with the addition of a flow that cannot exceed 133.49 liters/second. Keywords: Network flow, Maximum flow, Ford Fulkerson algorithm, Dinic algorithm
{"title":"Optimization of water flow on Regency Municipality Waterworks-network of Jonggat Central Lombok Regency using Ford Fulkerson Algorithm and Dinic Algorithm","authors":"Lilis Sriwahyuni, M. Marwan, Z. Awanis","doi":"10.29303/emj.v6i1.157","DOIUrl":"https://doi.org/10.29303/emj.v6i1.157","url":null,"abstract":"Clean water is essential for humans which must be fulfilled for humans survival. The population in Jonggat, Central Lombok, increases from year to year which causes the using of clean water get an increase too. The necessity of rising clean water is not in line with the availability of water in nature, therefore the PDAM (Regency Municipality Waterworks) manages existing water resource. Then, it will be distributed to consumers. The purpose of this research is to determine the optimal solution in the distribution of clean water in Jonggat using Ford Fulkerson algorithm and Dinic algorithm. Both Ford Fulkerson algorithm and Dinic algorithm are methods used to calculate the maximum flow in a network. Based on the results of research using Python software on the Ford Fulkerson algorithm, the maximum current is 133 liters/second, while using the Dinic algorithm, the maximum current is 133.49 liters/second. Meanwhile, the average water flow is delivered by PDAM is 95 liters/second. It means, it can be added the amount of flow in the clean water distribution pipe by the PDAM. It’s for facilitating the flow of water that reaches consumers with the addition of a flow that cannot exceed 133.49 liters/second. \u0000Keywords: Network flow, Maximum flow, Ford Fulkerson algorithm, Dinic algorithm","PeriodicalId":281429,"journal":{"name":"EIGEN MATHEMATICS JOURNAL","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131328743","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}
Rice has become the main staple food for almost the entire population of Indonesia. However, in Indonesia, the price of food commodities (rice) often fluctuates in price. Due to the rapid fluctuation of rice prices and the uncertainty in the future, it is necessary to forecast rice prices. This study aims to predict the price of rice in the city of Mataram using the Holt double exponential smoothing method and the Cheng fuzzy time series. The model's performance is based on Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE) indicators. Forecasting model based on Holt's double exponential smoothing method, the MSE value is 705967.4994 and the MAPE value is 7.91%. On the other hand, based on Cheng's fuzzy time series method, the performance of the forecasting model based on the MSE indicator is 566312.340 and based on the MAPE value of 6.75%. Based on these results, Cheng's fuzzy time series method is more accurate than Holt's double exponential smoothing method. Keywords: Double Exponential Smoothing Holt, Fuzzy Time Series Cheng, Rice Price, MAPE, MSE
{"title":"Peramalan Harga Beras dengan Metode Double Exponential Smoothing dan Fuzzy Time Series (Study Kasus : Harga Beras di Kota Mataram)","authors":"Sulpaiyah Sulpaiyah, syamsul bahri, Lisa Harsyiah","doi":"10.29303/emj.v5i2.123","DOIUrl":"https://doi.org/10.29303/emj.v5i2.123","url":null,"abstract":"Rice has become the main staple food for almost the entire population of Indonesia. However, in Indonesia, the price of food commodities (rice) often fluctuates in price. Due to the rapid fluctuation of rice prices and the uncertainty in the future, it is necessary to forecast rice prices. This study aims to predict the price of rice in the city of Mataram using the Holt double exponential smoothing method and the Cheng fuzzy time series. The model's performance is based on Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE) indicators. Forecasting model based on Holt's double exponential smoothing method, the MSE value is 705967.4994 and the MAPE value is 7.91%. On the other hand, based on Cheng's fuzzy time series method, the performance of the forecasting model based on the MSE indicator is 566312.340 and based on the MAPE value of 6.75%. Based on these results, Cheng's fuzzy time series method is more accurate than Holt's double exponential smoothing method. Keywords: Double Exponential Smoothing Holt, Fuzzy Time Series Cheng, Rice Price, MAPE, MSE","PeriodicalId":281429,"journal":{"name":"EIGEN MATHEMATICS JOURNAL","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122829207","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}
Baiq Urfa Justitiaski, N. Fitriyani, Syamsul Bahri
Infant mortality is death that occurs at the age of 0 to 1 year. According to the Provincial Health Office, East Lombok is the district with the largest infant mortality rate in NTB. Several factors influence infant mortality: childbirth with medical assistance, low birth weight, health facilities, health workers, and exclusive breastfeeding. These factors have a spatial influence because each region has different geographical, socio-cultural, and economic conditions. Therefore, the method that can be used is GWPR because it can model data with the response variable with a Poisson distribution and pay attention to location or spatial aspects. This study aims to determine the infant mortality model in East Lombok using Geographically Weighted Poisson Regression (GWPR) and to determine the factors that significantly influence the number of infant deaths in East Lombok. Based on the research conducted showed that low birth weight is the only factor that significantly affected infant mortality in 8 sub-districts, including Keruak, Sakra, West Sakra, East Sakra, Terara, Sukamulia, Selong, and Labuhan Haji. The model obtained gives a good estimator, with an R^2 value of 76,44%.
{"title":"Modeling the Number of Infant Mortality in East Lombok using Geographically Weighted Poisson Regression","authors":"Baiq Urfa Justitiaski, N. Fitriyani, Syamsul Bahri","doi":"10.29303/emj.v5i2.138","DOIUrl":"https://doi.org/10.29303/emj.v5i2.138","url":null,"abstract":"Infant mortality is death that occurs at the age of 0 to 1 year. According to the Provincial Health Office, East Lombok is the district with the largest infant mortality rate in NTB. Several factors influence infant mortality: childbirth with medical assistance, low birth weight, health facilities, health workers, and exclusive breastfeeding. These factors have a spatial influence because each region has different geographical, socio-cultural, and economic conditions. Therefore, the method that can be used is GWPR because it can model data with the response variable with a Poisson distribution and pay attention to location or spatial aspects. This study aims to determine the infant mortality model in East Lombok using Geographically Weighted Poisson Regression (GWPR) and to determine the factors that significantly influence the number of infant deaths in East Lombok. Based on the research conducted showed that low birth weight is the only factor that significantly affected infant mortality in 8 sub-districts, including Keruak, Sakra, West Sakra, East Sakra, Terara, Sukamulia, Selong, and Labuhan Haji. The model obtained gives a good estimator, with an R^2 value of 76,44%.","PeriodicalId":281429,"journal":{"name":"EIGEN MATHEMATICS JOURNAL","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114840257","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}
Ade Ima Afifa Himayati, Muhammad Adib Jauhari Dwi Putra, Erik Maurten Firdaus, Muhammad Faudzi Bahari
Peta wilayah kecamatan pada Kabupaten Grobogan dalat dioptimalisasi dengan algoritma Greedy. Titik pada graf mewakili kecamatan dan garis mewakili dua wilayah yang berbatasan langsung. Algoritma Greedy adalah salah satu algoritma yang dikembangkan untuk menyelesaikan masalah pewarnaan graf untuk dapat menghasilkan warna minimal yang digunakan tanpa ada warna yang sama pada wilayahyang berbatasan langsung. Algoritma Greedy menggunakan himpunan kandidat warna dan solusi dalam penyelesaiannya. Pewarnaan dilakukan pada titik dengan derajat terbesar dilanjutkan dengan pemeriksaan kelayakan warna dengan prinsip tidak ada titik bertetangga memiliki warna yang sama. Warna yang dihasilkan masuk dalam himpunan solusi. Proses dilanjutkan sampai semua titik selesai diwarnai. Pewarnaan wilayah di kabupaten Grobogan menghasilkan empat warna dengan Algoritma greedy sebagai solusi minimal warna yang diperoleh
{"title":"Application of the Greedy Algorithm for Graph Coloring of the Grobogan Regency Map","authors":"Ade Ima Afifa Himayati, Muhammad Adib Jauhari Dwi Putra, Erik Maurten Firdaus, Muhammad Faudzi Bahari","doi":"10.29303/emj.v5i2.149","DOIUrl":"https://doi.org/10.29303/emj.v5i2.149","url":null,"abstract":"Peta wilayah kecamatan pada Kabupaten Grobogan dalat dioptimalisasi dengan algoritma Greedy. Titik pada graf mewakili kecamatan dan garis mewakili dua wilayah yang berbatasan langsung. Algoritma Greedy adalah salah satu algoritma yang dikembangkan untuk menyelesaikan masalah pewarnaan graf untuk dapat menghasilkan warna minimal yang digunakan tanpa ada warna yang sama pada wilayahyang berbatasan langsung. Algoritma Greedy menggunakan himpunan kandidat warna dan solusi dalam penyelesaiannya. Pewarnaan dilakukan pada titik dengan derajat terbesar dilanjutkan dengan pemeriksaan kelayakan warna dengan prinsip tidak ada titik bertetangga memiliki warna yang sama. Warna yang dihasilkan masuk dalam himpunan solusi. Proses dilanjutkan sampai semua titik selesai diwarnai. Pewarnaan wilayah di kabupaten Grobogan menghasilkan empat warna dengan Algoritma greedy sebagai solusi minimal warna yang diperoleh","PeriodicalId":281429,"journal":{"name":"EIGEN MATHEMATICS JOURNAL","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126392345","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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