Pub Date : 2023-05-07DOI: 10.20473/conmatha.v5i1.44274
Muhammadun, Dieky Adzkiya, Imam Mukhlash
Sistem Max-Plus-Linear (MPL) adalah suatu kelas sistem event diskrit dengan ruang keadaan kontinu mengkarakterisasi sekuensial kejadian diskrit yang mendasari. Di literatur, ada pendekatan untuk analisis yang didasarkan pada abstraksi berhingga model MPL yang autonomous. Prosedur ini telah diimplementasikan dalam MATLAB dengan struktur data list/matriks/vektor. Kekurangan dari implementasi ini, operasi membuat transisinya membutuhkan waktu komputasi yang lama. Kemudian dilakukan perbaikan terhadap implementasi sebelumnya dalam JAVA dengan struktur data tree. Implementasi ini berhasil mempercepat waktu komputasinya tetapi membutuhkan alokasi memori yang lebih besar karena fungsi-fungsinya bersifat rekursif. Penelitian ini membahas implementasi prosedur abstraksi berhingga model MPL autonomous dalam C++ dengan menggunakan struktur data tree tanpa fungsi rekursif. Dari beberapa percobaan yang dilakukan, implementasi pada penelitian ini berhasil mempercepat waktu komputasi VeriSiMPL 2.0 secara signifikan
max - plu线性系统(MPL)是一个带有连续空间的离散事件系统类别，其基础是对离散事件序列的描述。从数据上看，有一种分析方法是基于autonomous MPL模型的抽象分析。这个过程已经在MATLAB上实现了列表/矩阵/向量数据结构。实现的缺陷是，进行变性手术需要很长时间的计算。然后在JAVA中对树数据结构的先前实现进行了改进。它的实现加快了计算时间，但需要更大的内存分配，因为它们的功能是递归的。本研究采用没有递归功能的tree数据结构，将从MPL autonomous在C+中实现抽象程序。在进行的几项实验中，这项研究的实现大大加快了VeriSiMPL 2.0的计算时间
{"title":"Desain dan Implementasi Perangkat Lunak Untuk Abstraksi Berhingga Sistem Max-Plus-Linear dengan Tree Tanpa Fungsi Rekursif","authors":"Muhammadun, Dieky Adzkiya, Imam Mukhlash","doi":"10.20473/conmatha.v5i1.44274","DOIUrl":"https://doi.org/10.20473/conmatha.v5i1.44274","url":null,"abstract":"Sistem Max-Plus-Linear (MPL) adalah suatu kelas sistem event diskrit dengan ruang keadaan kontinu mengkarakterisasi sekuensial kejadian diskrit yang mendasari. Di literatur, ada pendekatan untuk analisis yang didasarkan pada abstraksi berhingga model MPL yang autonomous. Prosedur ini telah diimplementasikan dalam MATLAB dengan struktur data list/matriks/vektor. Kekurangan dari implementasi ini, operasi membuat transisinya membutuhkan waktu komputasi yang lama. Kemudian dilakukan perbaikan terhadap implementasi sebelumnya dalam JAVA dengan struktur data tree. Implementasi ini berhasil mempercepat waktu komputasinya tetapi membutuhkan alokasi memori yang lebih besar karena fungsi-fungsinya bersifat rekursif. Penelitian ini membahas implementasi prosedur abstraksi berhingga model MPL autonomous dalam C++ dengan menggunakan struktur data tree tanpa fungsi rekursif. Dari beberapa percobaan yang dilakukan, implementasi pada penelitian ini berhasil mempercepat waktu komputasi VeriSiMPL 2.0 secara signifikan","PeriodicalId":119993,"journal":{"name":"Contemporary Mathematics and Applications (ConMathA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127842001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-07DOI: 10.20473/conmatha.v5i1.43176
M. Syaifuddin, Siti Zahidah, S.Si, M.Si, Eridani
This paper presents various forms of induction formulas and at the same time proves the equivalence of these formulas by proving that some of these formulas are equivalent to the Well-Ordering Principle which applies to natural number set.
{"title":"Tentang Rumus Induksi Matematika","authors":"M. Syaifuddin, Siti Zahidah, S.Si, M.Si, Eridani","doi":"10.20473/conmatha.v5i1.43176","DOIUrl":"https://doi.org/10.20473/conmatha.v5i1.43176","url":null,"abstract":"This paper presents various forms of induction formulas and at the same time proves the equivalence of these formulas by proving that some of these formulas are equivalent to the Well-Ordering Principle which applies to natural number set.","PeriodicalId":119993,"journal":{"name":"Contemporary Mathematics and Applications (ConMathA)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124754259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-07DOI: 10.20473/conmatha.v5i1.44637
Lilla Afiffah, Adinda Nur Ameliyah, A’idah Nur Hanifah, R. Artiono
Most of the plastic waste is generated by households. Plastic waste is often a problem because there are many and cannot decompose by itself. To solve the problem of plastic waste, plastic waste management will be carried out by channeling plastic waste to the waste bank. Good and correct management of plastic waste distribution is carried out by applying transportation methods starting from modeling the distribution of plastic waste generated from households and solutions from mathematical modeling that is built. From the transportation calculation, the minimum cost of managing the distribution of plastic waste will be obtained so that an efficient plastic waste distribution management system is formed. This study uses the type of experimental research (experimental research) with a literature study. The data used to construct the model are derived from literature studies and simulation data. The results of this study can be developed into a computer program regarding the management of household plastic waste distribution.
{"title":"Mathematical Modeling Of Household Plastic Waste Distribution Management With Transportation Methods","authors":"Lilla Afiffah, Adinda Nur Ameliyah, A’idah Nur Hanifah, R. Artiono","doi":"10.20473/conmatha.v5i1.44637","DOIUrl":"https://doi.org/10.20473/conmatha.v5i1.44637","url":null,"abstract":"Most of the plastic waste is generated by households. Plastic waste is often a problem because there are many and cannot decompose by itself. To solve the problem of plastic waste, plastic waste management will be carried out by channeling plastic waste to the waste bank. Good and correct management of plastic waste distribution is carried out by applying transportation methods starting from modeling the distribution of plastic waste generated from households and solutions from mathematical modeling that is built. From the transportation calculation, the minimum cost of managing the distribution of plastic waste will be obtained so that an efficient plastic waste distribution management system is formed. This study uses the type of experimental research (experimental research) with a literature study. The data used to construct the model are derived from literature studies and simulation data. The results of this study can be developed into a computer program regarding the management of household plastic waste distribution.","PeriodicalId":119993,"journal":{"name":"Contemporary Mathematics and Applications (ConMathA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132907589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-07DOI: 10.20473/conmatha.v5i1.44740
Nur Azizah, Kartika Nugraheni, Syalam Ali Wira Dinata
Dalam kehidupan, listrik merupakan salah satu sumber energi yang penting dan utama untuk memenuhi kebutuhan hidup manusia, baik dalam bidang industri, ekonomi maupun teknologi. Seiring dengan meningkatnya kebutuhan listrik dari waktu ke waktu, permasalahan yang dihadapi adalah kuantitas daya yang disalurkan, sehingga penyaluran listrik ke konsumen harus dioptimalkan sesuai dengan kebutuhan. Tujuannya agar dapat mengambil tindakan yang tepat berdasarkan kebutuhan listrik dan meningkatkan kualitas pelayanan kepada konsumen. Oleh karena itu, diperlukan metode peramalan beban listrik yang efektif di masa mendatang untuk mengoptimalkan kebutuhan listrik. Pada penelitian ini dilakukan peramalan dengan metode Triple SARIMA dengan menggunakan data sampel negara Denmark selama 60 menit dalam satuan Mega Watt yang diperoleh dari data sekunder open source (https://data.open-power-system-data.org/time_series/ 2020-10-06). Peramalan ini dilakukan dengan memperhitungkan faktor musiman harian, mingguan, dan tahunan. Tujuan dari penelitian ini adalah untuk mengetahui pola data beban listrik triple-seasonal terhadap pengaruh waktu periodik, mengevaluasi model triple-seasonal terbaik untuk mendapatkan minimum error dan model musiman subset, multiplicative dan additive. Hasil yang diperoleh dalam penelitian ini diperoleh 3 model sementara, kemudian dilakukan uji estimasi dan uji signifikansi dengan uji asumsi Maximum likelihood dan residual.
{"title":"Triple-Seasonal ARIMA Untuk Peramalan Data Konsumsi Beban Listrik","authors":"Nur Azizah, Kartika Nugraheni, Syalam Ali Wira Dinata","doi":"10.20473/conmatha.v5i1.44740","DOIUrl":"https://doi.org/10.20473/conmatha.v5i1.44740","url":null,"abstract":"\u0000Dalam kehidupan, listrik merupakan salah satu sumber energi yang penting dan utama untuk memenuhi kebutuhan hidup manusia, baik dalam bidang industri, ekonomi maupun teknologi. Seiring dengan meningkatnya kebutuhan listrik dari waktu ke waktu, permasalahan yang dihadapi adalah kuantitas daya yang disalurkan, sehingga penyaluran listrik ke konsumen harus dioptimalkan sesuai dengan kebutuhan. Tujuannya agar dapat mengambil tindakan yang tepat berdasarkan kebutuhan listrik dan meningkatkan kualitas pelayanan kepada konsumen. Oleh karena itu, diperlukan metode peramalan beban listrik yang efektif di masa mendatang untuk mengoptimalkan kebutuhan listrik. Pada penelitian ini dilakukan peramalan dengan metode Triple SARIMA dengan menggunakan data sampel negara Denmark selama 60 menit dalam satuan Mega Watt yang diperoleh dari data sekunder open source (https://data.open-power-system-data.org/time_series/ 2020-10-06). Peramalan ini dilakukan dengan memperhitungkan faktor musiman harian, mingguan, dan tahunan. Tujuan dari penelitian ini adalah untuk mengetahui pola data beban listrik triple-seasonal terhadap pengaruh waktu periodik, mengevaluasi model triple-seasonal terbaik untuk mendapatkan minimum error dan model musiman subset, multiplicative dan additive. Hasil yang diperoleh dalam penelitian ini diperoleh 3 model sementara, kemudian dilakukan uji estimasi dan uji signifikansi dengan uji asumsi Maximum likelihood dan residual. \u0000","PeriodicalId":119993,"journal":{"name":"Contemporary Mathematics and Applications (ConMathA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121873507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-07DOI: 10.20473/conmatha.v5i1.44103
Nashrul Millah
Traffic jams are common in developing countries. This is generally caused by traffic density, road conditions, and the driver's personality. This phenomenon can be simulated using a mathematical model, allowing it to be seen how these factors affect traffic conditions. The goal of this study is to simulate the effect of traffic density and road conditions using the Lighthill-Whitham-Richard (LWR) model. This model is used to describe macroscopic traffic flow conditions, which are affected by traffic density and speed. The Greenshield model with the influence of road condition parameters added is used for the speed. In numerical solutions, the Upwind method is used to evaluate midpoint values. The simulation results demonstrate the model's ability to describe traffic conditions that are affected by traffic density and road conditions. The level of traffic density is inversely proportional to road conditions and traffic speed.
交通堵塞在发展中国家很常见。这通常是由交通密度、道路状况和司机的性格造成的。这种现象可以用一个数学模型来模拟，从而可以看到这些因素是如何影响交通状况的。本研究的目的是利用lighhill - whitham - richard (LWR)模型模拟交通密度和道路条件的影响。该模型用于描述受交通密度和速度影响的宏观交通流状况。车速采用考虑路况参数影响的绿盾模型。在数值解中，采用逆风法求中点值。仿真结果表明，该模型能够描述受交通密度和道路状况影响的交通状况。交通密度水平与道路状况和交通速度成反比。
{"title":"Simulasi Numerik Model Arus Lalu Lintas dengan Pengaruh Kepadatan Kendaraan dan Kondisi Jalan","authors":"Nashrul Millah","doi":"10.20473/conmatha.v5i1.44103","DOIUrl":"https://doi.org/10.20473/conmatha.v5i1.44103","url":null,"abstract":"Traffic jams are common in developing countries. This is generally caused by traffic density, road conditions, and the driver's personality. This phenomenon can be simulated using a mathematical model, allowing it to be seen how these factors affect traffic conditions. The goal of this study is to simulate the effect of traffic density and road conditions using the Lighthill-Whitham-Richard (LWR) model. This model is used to describe macroscopic traffic flow conditions, which are affected by traffic density and speed. The Greenshield model with the influence of road condition parameters added is used for the speed. In numerical solutions, the Upwind method is used to evaluate midpoint values. The simulation results demonstrate the model's ability to describe traffic conditions that are affected by traffic density and road conditions. The level of traffic density is inversely proportional to road conditions and traffic speed.","PeriodicalId":119993,"journal":{"name":"Contemporary Mathematics and Applications (ConMathA)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121957535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-10DOI: 10.20473/conmatha.v4i2.38917
N. Chamidah, Ardi Kurniawan, T. Saifudin
Children would be categorized as children who have underweight nutritional status, if according to index of anthropometric they have a lack of weight. In Indonesia, this anthropometric index is recorded on a Card Toward Health called as KMS. This card follows the WHO-2005 standard which is designed based on samples from Brazil, Ghana, India, Norway, Oman, and USA. Those samples, of course, physically are very different from Indonesian children. Therefore, in this paper we design weight-for-age Z-score standard growth charts of children by using least-square spline estimator and samples of children from East Java province, Indonesia. Next, the proposed children standard growth charts are used to assess East Java children nutritional status. The results show that the proposed standard growth charts have met the goodness of fit criteria namely the average values of coefficient determination for boy and girl are close to one, and values of mean square errors are close to zero. It means that the proposed growth charts are more suitable to be used to assess the nutritional status of East Java children, because they can better explain the real conditions of children in East Java, Indonesia than the WHO-2005 standard growth charts.
{"title":"Designing Standard Growth Chart Based on Weight-For-Age Z-Score of Children in East Java Using Least-Square Spline Estimator","authors":"N. Chamidah, Ardi Kurniawan, T. Saifudin","doi":"10.20473/conmatha.v4i2.38917","DOIUrl":"https://doi.org/10.20473/conmatha.v4i2.38917","url":null,"abstract":"Children would be categorized as children who have underweight nutritional status, if according to index of anthropometric they have a lack of weight. In Indonesia, this anthropometric index is recorded on a Card Toward Health called as KMS. This card follows the WHO-2005 standard which is designed based on samples from Brazil, Ghana, India, Norway, Oman, and USA. Those samples, of course, physically are very different from Indonesian children. Therefore, in this paper we design weight-for-age Z-score standard growth charts of children by using least-square spline estimator and samples of children from East Java province, Indonesia. Next, the proposed children standard growth charts are used to assess East Java children nutritional status. The results show that the proposed standard growth charts have met the goodness of fit criteria namely the average values of coefficient determination for boy and girl are close to one, and values of mean square errors are close to zero. It means that the proposed growth charts are more suitable to be used to assess the nutritional status of East Java children, because they can better explain the real conditions of children in East Java, Indonesia than the WHO-2005 standard growth charts.","PeriodicalId":119993,"journal":{"name":"Contemporary Mathematics and Applications (ConMathA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115074781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-10DOI: 10.20473/conmatha.v4i2.39354
Marsya Anggun Prisila, Anna Islamiyati, A. K. Jaya
Regresi logistik biner dua level merupakan metode analisis regresi yang digunakan untuk menganalisis hubungan antara satu variabel respon yang berupa data kualitatif dikotomi dengan beberapa variabel prediktor, dari data yang berstruktur hirarki. Penelitian ini bertujuan untuk mendapatkan model data kepemilikan asuransi kesehatan di Indonesia berdasarkan status pekerjaan melalui analisis regresi logistik biner dua level. Metode yang digunakan adalah regresi logistik biner dua level dengan model random intercept menggunkan maximum likelihood estimation pada data kepemilikan asuransi kesehatan di Indonesia. Berdasarkan hasil taksiran model diperoleh bahwa status pekerjaan berpengaruh terhadap kepemilikan asuransi kesehatan di Indonesia dan 2.99 kali berpeluang memiliki asuransi kesehatan dibanding penduduk yang tidak memiliki pekerjaan.
{"title":"Model Data Kepemilikan Asuransi Kesehatan di Indonesia Berdasarkan Status Pekerjaan Melalui Analisis Regresi Logistik Biner Dua Level","authors":"Marsya Anggun Prisila, Anna Islamiyati, A. K. Jaya","doi":"10.20473/conmatha.v4i2.39354","DOIUrl":"https://doi.org/10.20473/conmatha.v4i2.39354","url":null,"abstract":"Regresi logistik biner dua level merupakan metode analisis regresi yang digunakan untuk menganalisis hubungan antara satu variabel respon yang berupa data kualitatif dikotomi dengan beberapa variabel prediktor, dari data yang berstruktur hirarki. Penelitian ini bertujuan untuk mendapatkan model data kepemilikan asuransi kesehatan di Indonesia berdasarkan status pekerjaan melalui analisis regresi logistik biner dua level. Metode yang digunakan adalah regresi logistik biner dua level dengan model random intercept menggunkan maximum likelihood estimation pada data kepemilikan asuransi kesehatan di Indonesia. Berdasarkan hasil taksiran model diperoleh bahwa status pekerjaan berpengaruh terhadap kepemilikan asuransi kesehatan di Indonesia dan 2.99 kali berpeluang memiliki asuransi kesehatan dibanding penduduk yang tidak memiliki pekerjaan.","PeriodicalId":119993,"journal":{"name":"Contemporary Mathematics and Applications (ConMathA)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127330151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-10DOI: 10.20473/conmatha.v4i2.39524
Hardy Batlajery, V. Ilwaru
This research focuses on the assignment of peer tutors in the Mathematics Study Program, Mathematics Department, FMIPA Unpatti. The purpose of this study was to obtain the completion of peer tutor assignments with the penalty method. The penalty method is a method used to solve the problem of unbalanced assignments. The processed two parts, namely finding the initial solution and finding the optimal solution. The column penalty method or the row penalty method is used to get the initial solution. In this study, the row penalty method is used because the number of rows is less than the number of columns, and the optimal solution is sought. The data used are student names, courses, and final grades. The results obtained using the Penalty method are that David becomes a tutor in the Statistical Method course, Alfito becomes a tutor in the Operations Research course, Christin becomes a tutor in the Linear Program course, Gabriella becomes a tutor in the Analytical Geometry course and Navila becomes a tutor in the course Elementary Statistics.
{"title":"Penugasan Tutor Sebaya dengan Metode Pinalti","authors":"Hardy Batlajery, V. Ilwaru","doi":"10.20473/conmatha.v4i2.39524","DOIUrl":"https://doi.org/10.20473/conmatha.v4i2.39524","url":null,"abstract":"This research focuses on the assignment of peer tutors in the Mathematics Study Program, Mathematics Department, FMIPA Unpatti. The purpose of this study was to obtain the completion of peer tutor assignments with the penalty method. The penalty method is a method used to solve the problem of unbalanced assignments. The processed two parts, namely finding the initial solution and finding the optimal solution. The column penalty method or the row penalty method is used to get the initial solution. In this study, the row penalty method is used because the number of rows is less than the number of columns, and the optimal solution is sought. The data used are student names, courses, and final grades. The results obtained using the Penalty method are that David becomes a tutor in the Statistical Method course, Alfito becomes a tutor in the Operations Research course, Christin becomes a tutor in the Linear Program course, Gabriella becomes a tutor in the Analytical Geometry course and Navila becomes a tutor in the course Elementary Statistics.","PeriodicalId":119993,"journal":{"name":"Contemporary Mathematics and Applications (ConMathA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115909397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-10DOI: 10.20473/conmatha.v4i2.39168
Bertha Aurellia Pamudya Fajar, Miswanto, Windarto
Influenza is a respiratory tract infection known as flu. Caused by an RNA virus from Orthomyxoviridae family. This thesis aims to analyze the stability of the equilibrium point in the mathematical model of influenza transmission with Cross-Immune population and applying optimal control variables in the form of prevention and treatment. In this mathematical model of influenza transmission with Cross-Immune population, we obtain two equilibriums namely, the non- endemic equilibrium and the endemic equilibrium. Local stability and the existence of endemic equilibrium depend on the basic reproduction number (R0). The spread of influenza does not occur in the population when R0 < 1 and the spread of influenza persist in the population when R0 > 1. Furthermore, the problem of control variables in the mathematical model of influenza transmission is determined through the Pontryagin Maximum Principle method. The numerical simulation results show that treatment efforts are more effective in suppressing the spread of influenza disease than prevention efforts. However, giving control variables in the form of prevention and treatment at the same time is very effective in minimizing the number of human populations expose to and infected with influenza.
{"title":"Analisis Kestabilan dan Kontrol Optimum pada Model Penyebaran Penyakit Influenza dengan Adanya Populasi Cross-Immune","authors":"Bertha Aurellia Pamudya Fajar, Miswanto, Windarto","doi":"10.20473/conmatha.v4i2.39168","DOIUrl":"https://doi.org/10.20473/conmatha.v4i2.39168","url":null,"abstract":"Influenza is a respiratory tract infection known as flu. Caused by an RNA virus from Orthomyxoviridae family. This thesis aims to analyze the stability of the equilibrium point in the mathematical model of influenza transmission with Cross-Immune population and applying optimal control variables in the form of prevention and treatment. In this mathematical model of influenza transmission with Cross-Immune population, we obtain two equilibriums namely, the non- endemic equilibrium and the endemic equilibrium. Local stability and the existence of endemic equilibrium depend on the basic reproduction number (R0). The spread of influenza does not occur in the population when R0 < 1 and the spread of influenza persist in the population when R0 > 1. Furthermore, the problem of control variables in the mathematical model of influenza transmission is determined through the Pontryagin Maximum Principle method. The numerical simulation results show that treatment efforts are more effective in suppressing the spread of influenza disease than prevention efforts. However, giving control variables in the form of prevention and treatment at the same time is very effective in minimizing the number of human populations expose to and infected with influenza.","PeriodicalId":119993,"journal":{"name":"Contemporary Mathematics and Applications (ConMathA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127838657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-10DOI: 10.20473/conmatha.v4i2.38262
Fiqih Fathor Rachim, A. Damayanti, E. Winarko
Consumer reviews are opinions from buyers to sellers based on service satisfaction or product quality. The more consumer reviews cause the process of analyzing manually will be difficult. Therefore, an automated sentiment analysis system is needed. Each review will be grouped into a sentiment class which is divided into positive and negative classes. This study aims to classify review texts using the Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) methods. The research stages in this study include collecting data on Tokopedia review texts, extracting hidden information from review texts using CNN, conducting learning on review texts using GRU. A total of 1000 review texts were divided into 80% training data and 20% test data. The review text is converted into matrix using One Hot Encoding algorithm and then extracted using CNN. The CNN process includes the convolution calculation, the calculation of the Rectified Linear Unit (ReLU) activation function, and the pooling stage. The extraction results in the CNN process are continued in the GRU process. The GRU process includes initializing parameters, GRU feed forward, Cross-Entropy Error calculation, GRU feedback, and updating weights and biases. The optimal weight is obtained when the error value in the training is less than the expected minimum error or the training iteration has reached the specified maximum iteration. Optimal weight is used for validation test on test data. The implementation of review text classification using the hybrid Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) method was made using the python programming language. The accuracy of the validation test is 88.5%
消费者评论是买家对卖家基于服务满意度或产品质量的意见。用户评论越多，手动分析的过程就越困难。因此，需要一个自动化的情感分析系统。每个评论将被分组到一个情绪类中，分为积极类和消极类。本研究旨在使用卷积神经网络(CNN)和门控循环单元(GRU)方法对评论文本进行分类。本研究的研究阶段包括收集Tokopedia复习文本的数据，使用CNN提取复习文本中的隐藏信息，使用GRU对复习文本进行学习。1000篇复习文本被分成80%的训练数据和20%的测试数据。使用One Hot Encoding算法将评论文本转换成矩阵，然后使用CNN进行提取。CNN过程包括卷积计算、ReLU (Rectified Linear Unit)激活函数的计算和池化阶段。在GRU过程中延续了CNN过程中的提取结果。GRU过程包括初始化参数、GRU前馈、交叉熵误差计算、GRU反馈以及权重和偏差的更新。当训练中的误差值小于期望的最小误差或训练迭代达到指定的最大迭代时，获得最优权值。采用最优权值对试验数据进行验证试验。使用python编程语言实现了基于卷积神经网络(CNN)和门控循环单元(GRU)混合方法的评论文本分类。验证试验的准确度为88.5%
{"title":"Classification of Review Text using Hybrid Convolutional Neural Network and Gated Recurrent Unit Methods","authors":"Fiqih Fathor Rachim, A. Damayanti, E. Winarko","doi":"10.20473/conmatha.v4i2.38262","DOIUrl":"https://doi.org/10.20473/conmatha.v4i2.38262","url":null,"abstract":"Consumer reviews are opinions from buyers to sellers based on service satisfaction or product quality. The more consumer reviews cause the process of analyzing manually will be difficult. Therefore, an automated sentiment analysis system is needed. Each review will be grouped into a sentiment class which is divided into positive and negative classes. This study aims to classify review texts using the Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) methods. The research stages in this study include collecting data on Tokopedia review texts, extracting hidden information from review texts using CNN, conducting learning on review texts using GRU. A total of 1000 review texts were divided into 80% training data and 20% test data. The review text is converted into matrix using One Hot Encoding algorithm and then extracted using CNN. The CNN process includes the convolution calculation, the calculation of the Rectified Linear Unit (ReLU) activation function, and the pooling stage. The extraction results in the CNN process are continued in the GRU process. The GRU process includes initializing parameters, GRU feed forward, Cross-Entropy Error calculation, GRU feedback, and updating weights and biases. The optimal weight is obtained when the error value in the training is less than the expected minimum error or the training iteration has reached the specified maximum iteration. Optimal weight is used for validation test on test data. The implementation of review text classification using the hybrid Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) method was made using the python programming language. The accuracy of the validation test is 88.5%","PeriodicalId":119993,"journal":{"name":"Contemporary Mathematics and Applications (ConMathA)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117302977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：