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Khairul Alim
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Department of Mathematics Faculty of Science and Technology Universitas Jambi Kampus Pinang Masak Mendalo Jambi Indonesia
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Mathematical Sciences and Applications Journal
Published by Universitas Jambi
ISSN : -     EISSN : 29886481     DOI : https://doi.org/10.22437/msa.v4i2
Core Subject : Science, Education,
Decision Sciences, Operations Research & Management Mathematics
The scope of this journal including is Real Analysis Algebra Applied mathematics Computational Mathematics Applied Statistics Actuarial mathematics and others
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 18 Documents
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MODEL MULTILEVEL UNTUK MENENTUKAN FAKTOR YANG MEMPENGARUHI ANGKA KEMATIAN BAYI Ainun Mardia; vinny yuliani; Zawaqi Afdal Jamil
Mathematical Sciences and Applications Journal Vol. 1 No. 1 (2020): Mathematical Sciences and Applications Journal
Publisher : Department of Mathematics, Faculty of Science and Technology Universitas Jambi

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Abstract

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. Keywords: Babies Modeling, Mortality, Multilevel, Statistics
CLUSTERING ANALYSIS WITH AVERAGE LINKAGE METHOD FOR GROUPING PROVINCE IN INDONESIA BASED ON WELFARE INDICATORS dwiki Prasetia; sufri; gusmi kholijah
Mathematical Sciences and Applications Journal Vol. 1 No. 1 (2020): Mathematical Sciences and Applications Journal
Publisher : Department of Mathematics, Faculty of Science and Technology Universitas Jambi

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Abstract

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. Keywords: Cluster Analysis, Average Linkage, People's Welfare
PANEL 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) iga mawarni; Kamid; gusmi kholijah
Mathematical Sciences and Applications Journal Vol. 1 No. 1 (2020): Mathematical Sciences and Applications Journal
Publisher : Department of Mathematics, Faculty of Science and Technology Universitas Jambi

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Abstract

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%. Keywords: Fixed Effect, Panel Data Regression, Port Services
MODEL SIRS PADA PENYEBARAN PENYAKIT DIARE AKUT PADA BALITA DI PROVINSI JAMBI zulistia nabila; Kamid; niken rarasati
Mathematical Sciences and Applications Journal Vol. 1 No. 1 (2020): Mathematical Sciences and Applications Journal
Publisher : Department of Mathematics, Faculty of Science and Technology Universitas Jambi

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Abstract

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. Keywords: Stability, SIRS model, disease free equilibrium point and endemic equilibrium point.
Residues on Beta Function yulia mustika; cut
Mathematical Sciences and Applications Journal Vol. 1 No. 1 (2020): Mathematical Sciences and Applications Journal
Publisher : Department of Mathematics, Faculty of Science and Technology Universitas Jambi

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Abstract

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, ( dengan . and the parameter value contains infinite positive integers, then for each positive integer value entered in the Beta function produces a zero value residue. Keywords: Beta function, residue
Analisis Meta Hubungan antara Obesitas dan Risiko Diabetes Mellitus dengan Data Binary dan Odd Ratio menggunakan Model Random Effect Panji Jiblathar; Ellys Agustina
Mathematical Sciences and Applications Journal Vol. 4 No. 2 (2024): Mathematical Sciences and Applications Journal
Publisher : Department of Mathematics, Faculty of Science and Technology Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/msa.v4i2.28287

Abstract

Meta-analysis is a statistical technique used to combine the results of several primary studies that have been conducted previously, with the aim of obtaining stronger and more accurate conclusions than can be obtained from each primary study individually. In this case, meta-analysis is performed to evaluate the relationship between obesity and the risk of diabetes mellitus. The data used in this meta-analysis is binary data, which contains information about the presence or absence of diabetes mellitus in individuals who are obese. The odds ratio is used as a measure of effect, which is the ratio between the likelihood of diabetes mellitus in individuals who are obese compared to individuals who are not obese. The results of the meta-analysis show heterogeneity between the primary studies conducted. Therefore, random effects are used in the meta-analysis model. The results of the analysis show that there is a significant relationship between obesity and the risk of diabetes mellitus, with a high odds ratio value. The conclusion from this meta-analysis is that obesity significantly increases the risk of diabetes mellitus. This finding has important implications in efforts to prevent and treat diabetes mellitus, especially in individuals at high risk for obesity.
Penerapan Model Self-Exciting Threshold Autoregressive (SETAR) Nonlinear dalam Memodelkan Data Harga Minyak Sawit (FCPOc1) Yunus Iman Katabba; Kezia Estefani
Mathematical Sciences and Applications Journal Vol. 4 No. 1 (2023): Mathematical Sciences and Applications Journal
Publisher : Department of Mathematics, Faculty of Science and Technology Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/msa.v4i1.28292

Abstract

Palm oil is an agricultural commodity that has an important role in the global economy. Palm oil is obtained from the fruit of the oil palm tree (Elaeis guineensis) which grows in tropical regions, especially in countries such as Indonesia, Malaysia, Thailand and several West African countries. Palm oil has a variety of uses in the food, cosmetics and fuel industries, making it one of the most traded commodities in the world. Palm oil price fluctuations have a significant influence on the economy in producing and consuming countries. Therefore, a time series analysis is needed that can predict fluctuations caused by certain conditions. This analysis is carrying out nonlinear analysis using the SETAR (Self Exciting Threshold Autoregressive) method on palm oil prices to obtain a prediction model and prediction results for palm oil prices. The SETAR model is a special case part of the Threshold Autoregressive (TAR) model. The SETAR model threshold is a lag value of the series itself or the endogenous variable. Analysis carried out using the SETAR method produces a SETAR (3,1,1) model with threshold (r) = 0.01626070 where the fit value approaches the actual data value and the predicted value follows the actual data pattern
Analisis Tingkat Kesehatan Bank dengan Menggunakan Metode CAMELS pada PT. Bank Pembangunan Daerah Jambi Periode 2015-2019 Ellys Agustina; Panji Jiblathar
Mathematical Sciences and Applications Journal Vol. 4 No. 1 (2023): Mathematical Sciences and Applications Journal
Publisher : Department of Mathematics, Faculty of Science and Technology Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/msa.v4i1.28304

Abstract

The structured and integrated management of economic resources has a significant impact on a nation's economic growth. Banks, as crucial financial institutions, play a pivotal role in the stewardship of these economic resources. This article delves into an analysis of the banking health level using the CAMELS method for PT. Bank Pembangunan Daerah Jambi during the period from 2015 to 2019. The CAMELS method is employed to evaluate the bank's health across various indicators, encompassing Capital, Asset Quality, Management, Earnings, Liquidity, and Sensitivity to Market Risk. This assessment holds paramount importance given the micro and macro economics ramifications that banks exert on the economy. The analysis reveals that PT. Bank Pembangunan Daerah Jambi during the aforementioned period falls within the "Healthy" category based on CAMELS ratios. The Capital Adequacy Ratio (CAR) consistently exceeds 8%, and asset quality (Kualitas Aktiva Produktif - KAP) remains in a favorable category. The bank's management displays robust performance, with a commendable Net Profit Margin (NPM). Furthermore, the Return on Assets (ROA) also demonstrates a commendable performance. The bank maintains adequate liquidity with an appropriate Loan-to-Deposit Ratio (LDR). This analysis aids in assessing the bank's health and provides a deeper understanding of how it manages resources and risks. Consequently, PT. Bank Pembangunan Daerah Jambi appears to exhibit solid performance during this period, contributing to the economic stability of Jambi Province.
Bifurkasi Mundur dalam Model Matematika Penyebaran Penyakit Tuberkulosis dengan Mempertimbangkan Laju Deteksi dan Pengobatan Chrissytalia Finka Liantoko; Lusia Krismiyati Budiasih
Mathematical Sciences and Applications Journal Vol. 4 No. 1 (2023): Mathematical Sciences and Applications Journal
Publisher : Department of Mathematics, Faculty of Science and Technology Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/msa.v4i1.28500

Abstract

Tuberculosis is a disease caused by the bacteria Mycobacterium tuberculosis. This disease can spread bacteria from one individual to another. In this article, we analyzed the spread of Tuberculosis using the SEIR model. The mathematical model is presented in a system of first-order nonlinear ordinary differential equations. This mathematical model also observes the rate of case detection and treatment. This article also discusses the analysis of the equilibrium point, the stability of the equilibrium points of the model that has been formed, and the basic reproduction number (R0). This model shows a backward bifurcation, that is the appearance of an endemic equilibrium point when R0<1, which means that the disease will not necessarily disappear even though R0<1. The numerical solution for this model is obtained using the fifth order Runge-Kutta method.
Analisis Korelasi Pearson Total Unit Printed Circuit Board Assembly (PCBA) Good In Circuit Testing (ICT) Puri Rahayu Nengsi; Andini Setyo Anggraeni; Widya Reza
Mathematical Sciences and Applications Journal Vol. 4 No. 1 (2023): Mathematical Sciences and Applications Journal
Publisher : Department of Mathematics, Faculty of Science and Technology Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/msa.v4i1.28508

Abstract

Every job always faces challenges or problems from various aspects, one of the problems was related to PT PCI Elektronik Internasional's production target for In Circuit Testing (ICT), which aims to achieve 90% of the total ICT units as good product, it means that the minimum percentage of ICT units that must be good is 90% to achieve this target. However, not all units can be classified as 100% good. The quality of the ICT unit depends on the condition of the Printed Circuit Board Assembly (PCBA) and the testing machine. This research will analyze the relationship between the total PCBA good ICT units in May and June 2023 using correlation analysis. Based on the results of correlation analysis using the Pearson method, a correlation coefficient value of 0.843 was obtained between the total PCBA good ICT units in May 2023 and the total PCBA good ICT units in June 2023. The correlation value of 0.843 indicates that there is a strong positive linear relationship between the total PCBA good ICT units in May and June 2023.

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