https://online-journal.unja.ac.id/msa/issue/feedMathematics Science and Application Journal2020-10-26T20:12:43+07:00Gusmi Kholijahgusmikholijah@unja.ac.idOpen Journal Systems<p><span class="value"> Mathematics Science and Application Journal (MSA) is a peer-reviewed journal which is published by Jambi University (Mathematics Department, Science and Technology Faculty). Since 2020, this journal publishes biannually in April and Oktober, with scope field includes research in the field of algebra, statistics application, actuaria, and applied mathematics.<br /></span></p>https://online-journal.unja.ac.id/msa/article/view/10131MODEL MULTILEVEL UNTUK MENENTUKAN FAKTOR YANG MEMPENGARUHI ANGKA KEMATIAN BAYI 2020-10-26T20:10:30+07:00Ainun Mardiaainunmardia@uinjambi.ac.idvinny yulianivinnyyulianisundara@uinjambi.ac.idZawaqi Afdal Jamilzawaqi.ajdosen@uinjambi.ac.id<p>Infant mortality in Indonesia is a very worrying situation. There are so many factors that affect infant mortality in Indonesia. Broadly speaking, the factors that influence infant mortality in Indonesia are divided into two, namely endogenous and exogenous. Data on infant mortality is taken from Ministry of Health data. The data consists of 65 districts in Indonesia and 33 provinces in Indonesia. Data on infant mortality in Indonesia will be modeled using multilevel modeling with level one in the model being the district and level two in the model being the province in Indonesia.Multilevel modeling is structured hierarchical modeling. Multilevel modeling can analyze structured or stratified data. The results obtained from multilevel modeling for factors affecting infant mortality are that the variance in the province becomes greater when the district structure has been released in the model. This indicates that diversity within districts is only influenced by provincial diversity.Abstract is filled with 150-250 words in Indonesian. Written in Times New Roman font style and font size 12, space 1. Abstract content is a summary of the problem and purpose, research methods, results and conclusions.</p> <p>Keywords: Babies Modeling, Mortality, Multilevel, Statistics</p>2020-10-27T00:00:00+07:00Copyright (c) 2020 Mathematics Science and Application Journalhttps://online-journal.unja.ac.id/msa/article/view/10132CLUSTERING ANALYSIS WITH AVERAGE LINKAGE METHOD FOR GROUPING PROVINCE IN INDONESIA BASED ON WELFARE INDICATORS2020-10-26T20:12:43+07:00dwiki Prasetiadwikiprasetyasubakti@gmail.comsufrisufriary@yahoo.comgusmi kholijahgusmikholijah@unja.ac.id<p><em>The high level of social inequality in Indonesia is a problem that must be resolved immediately. High social inequality will result in an increase in social tension which also impacts on the high level of conflict and crime in society. The problem of social inequality can be solved by accelerating the welfare distribution program by the government. The provision of this program must be fair and adapted to the conditions needed by each region. This is because each region has different causes of welfare problems. Therefore, in providing the program, the government must have a priority scale on welfare issues in an area that can be done using a mathematical method in the field of statistics, namely cluster analysis. This study aims to obtain, analyze and interpret the results of grouping provinces in Indonesia based on indicators of people's welfare. As many as 34 provinces in Indonesia as objects will be grouped based on 20 variables related to people's welfare. The grouping is done using the Hierarchy Method, the agglomeration grouping procedure with the Average Linkage technique and the size of the Euclidean Distance. From the clustering algorithm, it was found that from 34 provinces in Indonesia grouped into 5 clusters namely Cluster 1 consisting of 24 members namely Aceh Province; North Sumatra; West Sumatra; Riau; Jambi; South Sumatra; Bengkulu; Lampung; Head of Pacific Islands; Riau Islands; West Java; Central Java; East Java; Banten; West Nusa Tenggara; Central Kalimantan; South Borneo; East Kalimantan; North Kalimantan; North Sulawesi; Central Sulawesi; South Sulawesi; Southeast Sulawesi; and Gorontalo. Cluster 2 consists of 1 member, DKI Jakarta Province. Cluster 3 consists of 2 members including DI Yogyakarta and Bali Provinces. Cluster 4 consists of 6 members including East Nusa Tenggara Province; West Kalimantan; West Sulawesi; Maluku; North Maluku; and West Papua. Cluster 5 consists of 1 member, Papua Province. Based on the comparison of the average value of each cluster, the five clusters are sorted based on their level of welfare, namely: Cluster 3 as a very good cluster, Cluster 2 as a better cluster, Cluster 1 as a good cluster, Cluster 4 as a pretty good cluster and cluster 5 as a less good claser.</em></p> <p><em> </em></p> <p><em>Keywords: Cluster Analysis, Average Linkage, People's Welfare</em></p> <p><em> </em></p>2020-10-27T00:00:00+07:00Copyright (c) 2020 Mathematics Science and Application Journalhttps://online-journal.unja.ac.id/msa/article/view/10133PANEL DATA REGRESSION ANALYSIS OF PORT SERVICES SERVICES TOWARDS RATE ACCEPTANCE NOT TAXES (PNBP) (Case Study: At the Class IV Harbor Authority and Kuala Tungkal Port Authority) 2020-10-26T20:12:05+07:00iga mawarniigamawarni289@gmail.comKamidkamid@unja.ac.idgusmi kholijahgusmikholijah@unja.ac.id<p>on-Tax State Revenue (PNBP) is the receipt of the central government that is not derived from taxation. One source of PNBP is direct services by the state, such as the use of services at the port. This type of service is used in the related sector activities of the shipping company. The more port activities are carried out, the service at the port is increasing, so that PNBP received will increase. PNBP data in this study is a combination of time series data and cross section data called panel data. This study aims to determine the type of service that significantly influences PNBP using the Panel Data Regression Analysis method. From the analysis it is concluded that the best regression model estimation is the Fixed Effect Model (FEM) with dummy variables. FEM model states that the regression coefficient for navigation variables is 0.090824, PUJK variable is 0.267160 and the number of ships (JK) variable is 0.472592. These three variables are positive which means they have a significant effect on the level of PNBP. The PUP variable has a negative value of -0.061411, which means that the PUP variable does not significantly influence the level of PNBP. The variability of PNBP level in FEM model can be explained by the Navigation Services, Shipping Services (PUP), Port of Services (PUJK) and Number of Vessels (JK) variables of 88.75%.</p> <p> </p> <p>Keywords: Fixed Effect, Panel Data Regression, Port Services</p>2020-10-27T00:00:00+07:00Copyright (c) 2020 Mathematics Science and Application Journalhttps://online-journal.unja.ac.id/msa/article/view/10134MODEL SIRS PADA PENYEBARAN PENYAKIT DIARE AKUT PADA BALITA DI PROVINSI JAMBI2020-10-26T20:11:12+07:00zulistia nabilazulistianabila.zn@gmail.comKamidkamid@unja.ac.idniken rarasatinikenrarasati@unja.ac.id<p>This study aims to obtain a SIRS mathematical model on the spread of acute diarrheal disease in infants, find out the equilibrium point of the model and test the stability of these points. It is assumed that the birth rate and natural death rate are considered the same, the population is homogeneous, there is one population that is toddlers, there is only diarrheal disease in the population, and infected individuals can recover from the disease will become vulnerable again and there is no rotela immunization in infants. Based on the obtained disease-free equilibrium point, the stability criteria are tested around the disease-free and endemic equilibrium point as seen from its basic reproductive number. The disease-free equilibrium point is asymptotic stable if the basic reproductive number is less than one and unstable if the basic reproduction number is more than one. Whereas the endemic equilibrium point is stable asymptotically if the reproduction number has more than one base. The results obtained from the disease free equilibrium point are .. As for the endemic equilibrium point of the disease . Basic reproduction numbers for disease-free equilibrium points are: and .The basic reproduction number for the endemic equilibrium point of the disease is equal to: ) or . This means that the disease-free equilibrium point has R_0 <1 then the system is stable Local asymptotic means that in the under five population in Jambi Province no one is infected and no one can transmit acute diarrheal disease and the endemic equilibrium point of the disease has so the local asymptotic stable system means that every infected individual can transmit acute diarrheal disease to an average of one individual is vulnerable so that within a certain period of time the disease spreads in the population.</p> <p> </p> <p>Keywords: Stability, SIRS model, disease free equilibrium point and endemic equilibrium point.</p> <p> </p>2020-10-27T00:00:00+07:00Copyright (c) 2020 Mathematics Science and Application Journalhttps://online-journal.unja.ac.id/msa/article/view/10135Residues on Beta Function2020-10-26T19:50:20+07:00yulia mustikayuliamustikaanggraini@gmail.comcutcutmultahadah@gmail.com<p>The Beta function is part of a special function in the form of an integral statement and the result form is twice the multiplication of factorial functions. The Beta function is part of an unnatural integral because it has infinite-value parameters, resulting in infinite functions. Beta function is symbolized as β which basically can be defined in real and complex numbers with certain conditions. Completion of Beta functions can use residues. Residue is the residual product of an equation that has a singular point. Residues are used in calculating the integration of complex functions on unnatural integrals. Then the residue can complete the Beta function. Residues in the Beta function use the analysis of the concept of residues by determining the convergence, analytical, and kesingularitas areas of the Beta function, a Beta function domain is obtained. The domain area can be used in expanding the Laurent series. Then you will get a pole or pole that will affect the calculation in obtaining residuals. Based on the results of the study, the Beta function has a singular point that causes the point is not analytic to the Beta function. The singular point occurs at the point , then the residual form in the Beta function with the n-level pole and the singular point forms the equation,</p> <p>( </p> <p>dengan .</p> <p>and the parameter value contains infinite positive integers, then for each positive integer value entered in the Beta function produces a zero value residue.</p> <p> </p> <p>Keywords: Beta function, residue</p>2020-10-27T00:00:00+07:00Copyright (c) 2020 Mathematics Science and Application Journal