cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota makassar,
Sulawesi selatan
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
 33   34   35   36   37 
Survival Analysis of Covid-19 Patients Based on Time of Recovery Rina Widyasari; Muhammad Chairul Imam; Ramya Rachmawati; Rina Filia Sari
Jurnal Matematika, Statistika dan Komputasi Vol. 18 No. 3 (2022): MAY, 2022
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v18i3.18338

Abstract

Corona virus is a virus that can cause the respiratory tract to become infected, and this viral infection is called COVID-19. This virus spreads so fast that it has spread to several countries, including Indonesia. In Indonesia, COVID-19 was detected in early March, precisely on March 2, 2020. The uncertain increase in the number of COVID-19 patients will have an impact on society and the country. This condition is compounded by the high number of deaths due to the COVID-19 virus. Therefore, this study was conducted to analyze survival based on the healing rate of COVID-19 patients, in order to obtain information about the time period and the factors that cause a person with COVID-19 to survive. The method used in the survival analysis is the Kaplan-Meier test as a counter to the estimated recovery time of COVID-19 patients and the Log-Rank test to test for differences in the survival function of the recovery time of COVID-19 patients in the two groups. Kaplan-Meier and Log-Rank tests are part of the non-parametric method which is a statistical test that does not require any assumptions about the distribution of population data. The data used is data on COVID-19 patients at the Malahayati Hospital from January to May 31, 2021. The conclusion obtained is the survival function curve / length of time on the recovery rate of COVID-19 patients based on gender, age, and positive and suspected COVID-19 patients. with and without comorbidities. However, based on the Log-Rank test with = 0.05, it was concluded that there was no significant difference in the length of time for recovery of COVID-19 patients based on gender, age and positive patients and patients with suspected COVID-19 with comorbid and without comorbidities.
Clustering and Forecasting of Covid-19 Data in Indonesia Diyah Astuti; Dyah Yunita hartanti; Susi Tri Nurhayanti; Herlin Fransiska
Jurnal Matematika, Statistika dan Komputasi Vol. 18 No. 3 (2022): MAY, 2022
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v18i3.18882

Abstract

Indonesia reported its first case of Covid-19 in March 2020, which was suspected to have been infected by a foreigner who visited Indonesia. The distribution of cases that occurred in Indonesia has an uneven frequency considering that Indonesia is an archipelagic country, in the analysis of Covid-19 cases in Indonesia, there are many provinces and some have the same pattern of case characteristics. time series so that forecasting analysis can be used. So that clustering analysis and forecasting of Covid-19 data can be used in Indonesia. The analysis was carried out with 2 stages of analysis, namely clusters using the clustering hierarchy method and forecasting using the ARIMA method. By using 288 data from January 1, 2021 – October 15, 2021, the results show that the daily Covid-19 cases by province in Indonesia can be grouped into 2 clusters, in the forecasting analysis only one province is taken from each cluster used in determining the model, cluster 1 used data from the province of Banten and cluster 2 used data from the province of West Java. By using R software, a model for each cluster is obtained, namely ARIMA(0,1,1) for cluster 1 and ARIMA(2,1,2) for cluster 2. From the forecasting results obtained data until October 30, 2021 shows the number of cases tends to be constant.
Algoritma Support Vector Machine, Conditional Inference Trees, dan Random Forest untuk Klasifikasi Capaian Belajar Siswa SMP di Indonesia Tahun 2019 Alfina Nurpiana; Arie Wahyu Wijayanto
Jurnal Matematika, Statistika dan Komputasi Vol. 18 No. 3 (2022): MAY, 2022
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v18i3.19208

Abstract

Indonesian JHS students' learning achievement is still low. During 2015-2019, the average national exam score for Indonesian JHS has always decreased. In the last national examination, the average national exam score was 52.82 and was included in the bad category. This certainly needs to be a concern for local governments and the education office. Therefore, it is necessary to form a classification model that can be used to identify cities/districts in Indonesia which are categorized as bad or enough. This study discusses the comparison of models for the classification of learning achievement categories as seen from the average 2019 JHS results in 514 districts/cities in Indonesia using the Support Vector Machine (SVM), Conditional Inference Trees (Ctree), and Random Forest (RF) algorithms. The three algorithms were chosen because of their respective advantages, namely the SVM algorithm is known to be very powerful, Ctree as an improvement from the usual decision tree, and RF to represent ensemble learning. The independent variables used are education budget, classroom conditions, school accreditation, and teacher qualifications. From the results of this study, it has been found that the SVM algorithm produces the highest accuracy (0,80), recall (0,97), kappa statistics (0,38), and F1-score (0,87) compared to the Ctree and RF algorithms, while only precision (0,80) has the same value as the Ctree algorithm. So, the SVM algorithm produces the best model for the classification of district/city learning achievement categories in Indonesia based on education budget, classroom conditions, school accreditation, and teacher qualifications.
Analisis Dinamik Model Mangsa Pemangsa dengan Efek Allee Ganda dan Fungsi Respon Holling Tipe II Ismi Ra'yan Syarif; Syamsuddin Toaha; Jeffry Kusuma
Jurnal Matematika, Statistika dan Komputasi Vol. 18 No. 3 (2022): MAY, 2022
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v18i3.19237

Abstract

In this article, a predator prey model with double Allee effects and Holling type II functional response is discussed. Strong and weak Allee effects were analyzed separately. The dynamic behavior of the model is analyzed by determining the equilibrium point and stability around the equilibrium point. From the analysis result, it is obtained that the trivial equilibrium point is locally asymptotically stable for the case of the strong Allee effect and the saddle unstable for the case of the weak Allee effect, while the boundary and coexistence equilibrium points are locally asymptotically stable if it satisfies several parameter conditions. Numerical simulations are carried out around the coexistence equilibrium point. The simulation results show that the Allee effect threshold affects prey population growth when experiencing a strong Allee effect. The growth of the prey population also depends on the initial conditions of the prey and predator population density. Furthermore, when the prey population experiences a weak Allee effect, there is no threshold must be exceeded for the population to survive so that for each initial condition however, the population will not experience extinction.
Analisis Misklasifikasi Data Akreditasi Sekolah Dasar Di Kota Ambon Menggunakan Metode Multivariate Adaptive Regression Spline Sarah Risambessy; Salmon Notje Aulele; Ferry Kondo Lembang
Jurnal Matematika, Statistika dan Komputasi Vol. 18 No. 3 (2022): MAY, 2022
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v18i3.19451

Abstract

Many classification methods have been developed, one of which is the Multivariate Adaptive Regression Spline (MARS) method. MARS is one of the classification methods in the form of a combination of Recursive Partitioning Regression (RPR) and the spline method that is able to process high-dimensional and large-sized data and process data with continuous or binary response variables. The purpose of this study was to measure the misclassification of elementary school accreditation in Ambon city using the MARS method. This study uses accreditation data with the results of eight components of accreditation in elementary schools that have accreditation A (group 1) and accreditation B (group 2) in Ambon city. To evaluate the classification method used the APER classification error measure. The best classification result from the MARS method is when using a combination of BF=32, MI=3, MO=1 because it produces a minimum Generalized Cross Validation (GCV) of 0.066 and information is obtained that the correct classification data is 181 and the misclassified data is 10. Based on the results of the analysis, the size of the APER classification error is 5.23%, which can be said that the MARS method is good or statistically significant for classifying elementary schools in Ambon City based on their accreditation rating.  
Analisis Kestabilan Model Matematika Penyebaran Penyakit Tuberkulosis yang Koinfeksi Diabetes Melitus dengan Pengobatan strategi DOTS Mutmainnah Syamsul; Syamsuddin Toaha; Kasbawati Kasbawati
Jurnal Matematika, Statistika dan Komputasi Vol. 18 No. 3 (2022): MAY, 2022
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v18i3.19523

Abstract

Tuberculosis (TB) is an infectious disease caused by the bacterium Mycobacterium tuberculosis. Patients with symptoms of TB can be caused by immune disorders such as diabetes mellitus infection. Patients with diabetes mellitus can affect the clinical symptoms of TB patients and are associated with a slow response to TB treatment. This study aims to analyze and determine the stability of the equilibrium point of the TB disease spread model coinfected with DM by considering nine compartments, namely susceptible TB without DM, exposed TB without DM, infected TB without DM, recovered TB without DM, susceptible TB with DM, exposed TB with DM, infected TB with DM, recovered TB with DM, and treatment with DOTS. The research method used is a qualitative method by determining the basic reproduction number obtained with next generation matrix method to analyze the stability of the non-endemic and endemic equilibrium points. The non-endemic and endemic equilibrium points are said to be locally asymptotically stable if  , and unstable if  .The results obtained from sensitivity analysis show that the spread of disease can be reduced and eliminated if treated with DOTS in the infected compartment.
Perbandingan Fungsi Pembobot Kernel pada Geographically Weighted Logistic Regression dalam Memodelkan Kasus Kemiskinan di Indonesia Muftih Alwi Aliu; Fahrezal Zubedi; Lailany Yahya; Franky Alfrits Oroh
Jurnal Matematika, Statistika dan Komputasi Vol. 18 No. 3 (2022): MAY, 2022
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v18i3.19567

Abstract

Indonesia is a developing country that is facing poverty. The percentage of the poor population in Indonesia in 2020 increased by 0.97 percent from 2019. A suitable analysis to overcome poverty in Indonesia is the regional effect, namely Geographically Weighted Logistic Regression (GWLR). This study aimed to compare the weighting functions of the Fixed Gaussian Kernel, Fixed Tricube Kernel, and Fixed Bisquare Kernel in the GWLR model in modeling poverty in Indonesia in 2020. The best model can determine significant factors that affected poverty in Indonesia in 2020. This study used the percentage data of poor population  and the factors affecting it, namely the Open Unemployment Rate , Human Development Index , and Total Population  in 34 Provinces in Indonesia. This study indicates that the GWLR model with the Fixed Gaussian Kernel weighting function is the best in modeling poverty in Indonesia in 2020 based on the smallest Akaike Information Criterion Corrected (AlCc) value. The GWLR model with the Fixed Gaussian Kernel weighting function shows the Open Unemployment Rate as a significant factor affecting poverty in Indonesia in 2020 in 10 provinces in Indonesia, namely Aceh, North Sumatra, West Sumatra, Riau, Jambi, South Sumatra, Bengkulu, Lampung, DKI Jakarta, and Banten.  
Metode Ensemble K-Nearest Neighbor untuk Prediksi Indeks Harga Saham Gabungan (IHSG) di Indonesia Moh. Jusman; Nur’eni Nur’eni; Lilies Handayani
Jurnal Matematika, Statistika dan Komputasi Vol. 18 No. 3 (2022): MAY, 2022
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v18i3.19641

Abstract

The Composite Stock Price Index (CSPI) is a guide for investors to see the movement of stock prices as a whole from time to time. These movements always change from time to time, so it is necessary to use analytical methods to make predictions. The method that can be used to examine this is the K-Nearest Neighbor method. The combination of the results of several K-NN predictions is an effective way to get one final prediction result, namely the method ensemble K-NN. The response variable used in this study is the Composite Stock Price Index (CSPI), while the predictor variables are the gold price, the rupiah exchange rate against the dollar, and the Dow Jones Industrial Average (DJIA) index. The data used are 52 periods. The data used for training are 39 periods and the data used for testing is 13 periods. The prediction results from the ensemble have better results than the K-NN. The prediction results from the ensemble have better results than the single K-NN. The prediction results from the method are ensemble K-NN average of 6078, 634 with a MAPE value of 7,16% including high accuracy
Analisis Kestabilan dan Bifurkasi pada Model Matematika Penyebaran Penyakit Meningitis dengan Perlakuan Vaksinasi dan Pengobatan Rabiatul Adawiyah; Syamsuddin Toaha; Kasbawati Kasbawati
Jurnal Matematika, Statistika dan Komputasi Vol. 18 No. 3 (2022): MAY, 2022
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v18i3.19714

Abstract

Meningitis is an infectious disease that occurs in inflammation of the meninges and the spinal cord in consequence of bacteria and viruses. Vaccination and treatment using antibiotics is used to increase growth rate in infected people so that the spread rate can be reduced. This study aims to see the effect of vaccination and treatment using some compartments:  susceptible, carrier, infected without symptoms, infected with symptoms, recovery without disability, and recovery with disability; show the sensitivity analysis in order to discover the parameter that affect basic reproduction number and bifurcations analysis. The result from sensitivity found the relation between parameter and  that can increase and decrease the  value. This study also showed the influence of stability change from equilibrium point caused by the parameter  value change form bifurcations analysis. Models simulation show that the effect of vaccination and treatmen for spread of meningitis can be handled.
Regresi Binomial Negatif Bivariat untuk Pemodelan Kasus Konfirmasi dan Kasus Kematian akibat Covid-19 di Kalimantan Muhammad Luthfi Setiarno Putera
Jurnal Matematika, Statistika dan Komputasi Vol. 18 No. 3 (2022): MAY, 2022
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v18i3.19947

Abstract

Coronavirus disease (Covid-19) caused a pandemic severely affecting various sectors and paralyzed health services in Indonesia. As of June 2020, the percentage of Covid-19 confirmed cases in Kalimantan, the second largest island in Indonesia, contributed about 7% of the total national cases. In the same period, the percentage of Covid-19 deaths reached 12% of the national figure. This study used regression models to respond to bi-response count data consisting of Covid-19 confirmed cases and Covid-19 deaths in regencies/cities in Central Kalimantan and South Kalimantan provinces. This study compared the results of bivariate Poisson regression and bivariate negative binomial regression. There were thirteen predictors representing the determinants of health, social, economic, and demography indicators. The results showed that the prevalence of pneumonia had positive effect on Covid-19 confirmed cases and Covid-19 deaths. The percentage of elderly had negative effect on confirmed cases, while it had no significant effect on Covid-19 deaths. Bivariate negative binomial regression showed more satisfying performance on modeling Covid-19 cases and Covid-19 deaths jointly because it produced lower AIC and deviance than that of Poisson one. The negative bivariate model was also better than the Poisson one because it was able to overcome over-dispersion.  

Page 35 of 50 | Total Record : 496

 33   34   35   36   37 

Filter by Year

2005 2025


Reset
Filter By Issues
All Issue Vol. 21 No. 2 (2025): JANUARY 2025 Vol. 21 No. 1 (2024): SEPTEMBER 2024 Vol. 20 No. 3 (2024): May 2024 Vol. 20 No. 2 (2024): JANUARY 2024 Vol. 20 No. 1 (2023): SEPTEMBER, 2023 Vol. 19 No. 3 (2023): MAY, 2023 Vol. 19 No. 2 (2023): JANUARY 2023 Vol. 19 No. 1 (2022): SEPTEMBER, 2022 Vol. 18 No. 3 (2022): MAY, 2022 Vol. 18 No. 2 (2022): JANUARY 2022 Vol. 18 No. 1 (2021): September 2021 Vol. 17 No. 3 (2021): May, 2021 Vol. 17 No. 2 (2021): JANUARY 2021 Vol. 17 No. 1 (2020): JMSK, SEPTEMBER, 2020 Vol. 16 No. 3 (2020): JMSK, MAY, 2020 Vol. 16 No. 2 (2020): JMSK, JANUARY, 2020 Vol. 15 No. 2 (2019): JMSK Vol. 15, No. 2, January 2019 Vol. 16 No. 1 (2019): JMSK, July, 2019 Vol. 15 No. 1 (2018): July 2018 Vol. 14 No. 2 (2018): January 2018 Vol. 14 No. 1 (2017): July 2017 Vol. 13 No. 2 (2017): January 2017 Vol. 13 No. 1: July 2016 Vol. 12 No. 2: January 2016 Vol. 12 No. 1: July 2015 Vol. 11 No. 2: January 2015 Vol. 11 No. 1: July 2014 Vol. 10 No. 2: January 2014 Vol. 10 No. 1: July 2013 Vol. 9 No. 2: January 2013 Vol. 9 No. 1: July 2012 Vol. 8 No. 2: January 2012 Vol. 8 No. 1: July 2011 Vol. 7 No. 2: January 2011 Vol. 7 No. 1: July 2010 Vol. 6 No. 2: January 2010 Vol. 6 No. 1 (2009): July 2009 Vol. 5 No. 2: January 2009 Vol. 5 No. 1: July 2008 Vol. 4 No. 2: January 2008 Vol. 4 No. 1: July 2007 Vol. 3 No. 2: January 2007 Vol. 3 No. 1: July 2006 Vol. 2 No. 2: January 2006 Vol. 2 No. 1: July 2005 More Issue