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INDONESIA
JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI
Published by Universitas Hasanuddin
ISSN : 18581382     EISSN : 26148811     DOI : -
Core Subject : Education,
Mathematics
Jurnal ini mempublikasikan paper-paper original hasil-hasil penelitian dibidang Matematika, Statistika dan Komputasi Matematika.
Arjuna Subject : -
Articles 496 Documents
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Stability Analysis of Divorce Dynamics Models Syamsir Muaraf; Syamsuddin Toaha; Kasbawati Kasbawati
Jurnal Matematika, Statistika dan Komputasi Vol. 17 No. 2 (2021): JANUARY 2021
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/jmsk.v17i2.11984

Abstract

This article examines the mathematical model of divorce. This model consists of four population classes, namely the Married class (M), the population class who experiences separation of separated beds (S), the population class who is divorced by Divorce (D), and the population class who experiences depression or stress due to divorce Hardship (H). This study focuses on the stability analysis of divorce-free and endemic equilibrium points. Local stability was analyzed using linearization and eigenvalues ​​methods. In addition, the basic reproduction number  is provided via the next generation matrix method. The existence and stability of the equilibrium point are determined from . The results showed that the rate of interaction between population M and populations other than H is very influential on efforts to minimize divorce. Divorce can be minimized when the transmission rate is reduced to . Reducing the transmission rate and increasing the rate of transfer from split bed class to married class can turn divorce endemic cases into non-endemic cases. A numerical simulation is given to confirm the analysis results.
Analisis Kestabilan Model Matematika Sistem Respon Inflamasi Akibat Infeksi SARS Coronavirus Ario Wiraya
Jurnal Matematika, Statistika dan Komputasi Vol. 17 No. 2 (2021): JANUARY 2021
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/jmsk.v17i2.11995

Abstract

Severe Acute Respiratory Syndrome (SARS) Coronavirus infection in a human body indicated by cytokine response due to an inflammation. The purpose of this research is to construct and analyze a mathematical model of interaction between inflammatory pro-response and anti-response cytokine to predict the dynamic on inflammatory response system, so that the treatment can be optimized. The results obtained in this research describe some dynamics which happen on the cytokines, i.e. the disease-free equilibrium point is asymptotically stable when the basic reproduction number is less than one. In this condition, a patient with initial concentrations of the cytokines around the disease-free equilibrium point will be free of viral infection. The infection equilibrium point is asymptotically stable when the basic reproduction number is greater than one. In this condition, a patient with initial concentrations of the cytokines around the infection equilibrium point will be infected by the virus. Probability of a patient being free of viral infection can increase if the production rate of the cytokines are decreased or the degradation rate of the cytokines are increased.
Analisis Bicluster Algoritma CC untuk Mengidentifikasi Pola Rawan Pangan di Indonesia Raditya Novidianto; Rini Irfani
Jurnal Matematika, Statistika dan Komputasi Vol. 17 No. 2 (2021): JANUARY 2021
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/jmsk.v17i2.12057

Abstract

Indonesia is known as an agricultural country. This means that most of the population work in the agricultural sector related to food. However, food insecurity still occurs in Indonesia. With the COVID-19 pandemic, the Food and Agriculture Organization (FAO) stated that there was a threat of food scarcity which had an impact on food insecurity conditions. This would undermine the second goal of the SDGs, which is to end hunger and create sustainable agriculture. The purpose of this study was to determine the spatial pattern of food insecurity in each province in Indonesia using the bicluster method. The data used are data from Susenas and Sakernas by BPS in 2019. Several studies show that the bicluster method with the CC algorithm shows that each province group has a different characteristic pattern. In the bicluster approach, the researcher runs parameter tuning to select the best parameter based on the Mean Square Residual in Volume (MSR / V). The CC algorithm tries to get a bicluster with a low MSR value, therefore the best parameter is the one that produces the smallest MSR / V value, in this study the smallest MSR / V is 0,01737 with δ = 0,01. The application of the CC biclustering algorithm to the food insecurity structure in Indonesia results in 5 bicluster. Bicluster 1 consists of 15 provinces with 8 variables, Bicluster 2 consists of 10 provinces with 5 variables, Bicluster 3 consists of 3 provinces with 7 variables, Bicluster 4 consists of 4 provinces with 4 variables and Bicluster 5 consists of 2 provinces with 5 variables. Biculster 4 represents a cluster of food insecurity areas with the characteristics of the bicluster P0, P1, P2 and calorie consumption of less than 1400 KKAL.
A Two-Dimensional Mathematical Model of Carbon Dioxide (CO2) Transport in Concrete Carbonation Proses Muhammad Nur -Hidayat; Jeffry Kusuma; Naimah Aris
Jurnal Matematika, Statistika dan Komputasi Vol. 17 No. 3 (2021): May, 2021
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v17i3.12227

Abstract

A new two-dimensional mathematical model was developed to describe the transport phenomena of carbon dioxide in concrete structures. By treating transport phenomena as a concrete carbonation process, a two-dimensional linear partial differential equation was derived based on the principle of mass balance and convective-dispersive Equation. It was found the analytical solution by the separation of variables method combined with some substitution approaches. The numerical results are presented to illustrate the practical application of this model.
Comparison of Zero Inflated Poisson (ZIP) Regression, Zero Inflated Negative Binomial Regression (ZINB) and Binomial Negative Hurdle Regression (HNB) to Model Daily Cigarette Consumption Data for Adult Population in Indonesia Drajat Indra Purnama
Jurnal Matematika, Statistika dan Komputasi Vol. 17 No. 3 (2021): May, 2021
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v17i3.12278

Abstract

Smoking is a habit that is not good for health. Smoking habits are generally practiced by adults but it is possible for teenagers to do so.The Report of Southeast Asia Tobacco Control Alliance (SEATCA) entitled The Tobacco Control Atlas, ASEAN Region shows that Indonesia is the country with the highest number of smokers in ASEAN, namely 65.19 million people. This figure is equivalent to 34 percent of the total population of Indonesia in 2016. Based on these data, the authors are interested in modeling the daily cigarette consumption data for adults in Indonesia obtained from the 2015 Indonesia Family Life Survey. The variables used include the variable amount of cigarette consumption, education, level of welfare and income per month. The author wants to compare the best model that can be used to model the daily cigarette consumption of adults in Indonesia. The models being compared are Zero Inflated Poisson Regression (ZIP), Zero Inflated Negative Binomial Regression (ZINB) and Binomial Negative Hurdle Regression (HNB). The comparison results of the three models obtained that the best model is the Zero Inflated Negative Binomial (ZINB) Regression model because it has the smallest Akaike's Information Criterion (AIC) value.
Optimal Control of Mathematical Models on The Dynamics Spread of Drug Abuse Nita Anggriani; Syamsuddin Toaha; Kasbawati Kasbawati
Jurnal Matematika, Statistika dan Komputasi Vol. 17 No. 3 (2021): May, 2021
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v17i3.12467

Abstract

This article examines the optimal control of a mathematical model of the spread of drug abuse. This model consists of five population classes, namely susceptible to using drugs (S), light-grade drugs (A), heavy-grade drugs (H), medicated drugs (T), and Recovery from drugs (R). The system is solved using the Pontryagin minimum principle and numerically by the forward-backward sweep method. Numerical simulations of the optimal problem show that with the implementation of anti-drug campaigns and strengthening of self-psychology through counseling, the spread of drug abuse can be eradicated more quickly. The implementation of campaigns and strengthening of self-psychology through large amounts of counseling needs to be done from the beginning then the proportion can be reduced until a certain time does not need to be given anymore. The use of control in the form of strengthening efforts to self-psychology through counseling means that it needs to be done in a longer time to prevent the spread of drug abuse.
Penyelesaian Persamaan Diferensial Biasa Menggunakan Metode Runge-Kutta Orde Keempat Paralel dengan Tiga Prosesor Iman Al Fajri; Hendra Mesra; Jeffry Kusuma
Jurnal Matematika, Statistika dan Komputasi Vol. 17 No. 3 (2021): May, 2021
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v17i3.12490

Abstract

This paper presents a derivation of the Runge-Kutta or fourth method with six stages suitable for parallel implementation. Development of a parallel model based on the sparsity structure of the fourth type Runge-Kutta which is divided into three processors. The calculation of the parallel computation model and the sequential model from the accurate side shows that the sequential model is better. However, generally, the parallel method will end the analytic solution by increasing the number of iterations. In terms of execution time, parallel method has advantages over sequential method.
Bahasa Indonesia: Bahasa Indonesia Puji Puspa Sari; Erna Tri Herdiani; Nurtiti Sunusi
Jurnal Matematika, Statistika dan Komputasi Vol. 17 No. 3 (2021): May, 2021
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v17i3.12629

Abstract

Outliers are observations where the point of observation deviates from the data pattern. The existence of outliers in the data can cause irregularities in the results of data analysis. One solution to this problem is to detect outliers using a statistical approach. The statistical approach method used in this study is the Minimum Vector Variance (MVV) algorithm which has robust characteristics for outliers. The purpose of this research is to detect outliers using the MVV algorithm by changing the data sorting criteria using the Robust Depth Mahalanobis to produce maximum detection. The results obtained from this study are that RDMMVV is superior to the observed value in showing the outliers and the location of the outliers in the data plot compared to DMMVV and MMVV.
ANALISIS RISIKO HARGA JUAL EMAS DAN INVESTASI SAHAM ANTAM MENGGUNAKAN EXPECTED SHORTFALL PADA MASA PANDEMI COVID-19 Dwi Sulistiowati; Maya Sari Syahrul; Ilham Dangu Rianjaya
Jurnal Matematika, Statistika dan Komputasi Vol. 17 No. 3 (2021): May, 2021
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v17i3.12779

Abstract

The Covid-19 pandemic caused the price of gold produced by PT Aneka Tambang (Antam) to experience a high increase following the world gold price, while stock investment decreased. Measuring risk is significant in financial analysis; this is related to investment funds, which are quite large and narrow about public funds. This study analyzes the risk data on Antam gold price and Antam stock closing price with an estimated Shortfall (ES). The method used to measure the risk of investing in stocks is ES. ES is the expectation of a conditional loss that exceeds Value at Risk (VaR). To compute ES data showing deviations from normality and Cornish-Fisher expansion. The volatility measurement model used is the autoregressive conditional heteroskedasticity (ARCH) and generalized ARCH (GARCH) model.This study found that the ES value of Antam gold price was smaller than Antam stock price.
Analisis Pengaruh BI 7-Days Repo Rate Terhadap Indeks Harga Saham Gabungan Menggunakan Pendekatan Regresi Nonparametrik Berdasarkan Estimator Least Square Spline Christopher Andreas; Feevrinna Yohannes Harianto; Elfhira Juli Safitri; Nur Chamidah
Jurnal Matematika, Statistika dan Komputasi Vol. 17 No. 3 (2021): May, 2021
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v17i3.13101

Abstract

During the Covid-19 pandemic, the Indonesia stock market was under great pressure, so that the value of the Jakarta Composite Index (JCI) fluctuated greatly. To maintain economic stability, Bank Indonesia has regulated monetary policy such as setting the BI 7-Days Repo Rate. Analysis of this effect is important to formulate the right policy. This study aims to design the best model in describing the relationship between JCI value and BI 7-Days Repo Rate. The analysis was carried out by using parametric regression approach based on the ordinary least square method and nonparametric regression approach based on least square spline estimator. The results showed that the parametric regression models failed to meet the classical assumptions. Meanwhile, nonparametric regression can produce an optimal model with high accurate prediction, with an overall mean absolute percentage error value of 3.16%. Furthermore, mean square error, coefficient of determination, and mean absolute deviation also show good results. Thus, the effect of the BI 7-Days Repo Rate on the JCI value forms a quadratic pattern, in which a positive relationship is formed when the BI 7-Days Repo Rate is set at more than 4.25% and vice versa for a negative relationship.

Page 31 of 50 | Total Record : 496

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