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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI NUMERICAL (Jurnal Matematika dan Pendidikan Matematika)
Muhammad Luthfi Setiarno Putera
Institut Agama Islam Negeri Palangka Raya
Mathematics

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Non-cash Payment Transaction Projection Using ARIMAX : Efect of Calendar Muhammad Luthfi Setiarno Putera
Jurnal Matematika, Statistika dan Komputasi Vol. 16 No. 3 (2020): JMSK, MAY, 2020
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (522.194 KB) | DOI: 10.20956/jmsk.v16i3.8546

Abstract

As the most Moslem country, economic activity in Indonesia is often parallel with the movement of Qamariah (lunar) calendar which is different with Gregorian calendar. Using calender variation, this research attempts to look for modified time series model for non-cash payment projection (forecast) aim. The result shows that calendar variation plays statistically significant role on non-cash payment, evidenced by significant payment in the month in which Eid Fitr occurs. The occurrence of Eid Fitr in the first and second week of the month is evidently characterized by increasing non-cash payment in one month earlier. The best model with highest accuracy for non-cash payment projection is ARIMAX(2,1,1) as it is able to capture the pattern, trend and fluctuation. It also suggests the peak of non-cash payment will be in December.
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.  
Spatial Regression Models on Factors Influencing Regional Minimum Wages Muhammad Luthfi Setiarno Putera
Numerical: Jurnal Matematika dan Pendidikan Matematika Vol. 4 No. 2 (2020)
Publisher : Institut Agama Islam Ma'arif NU (IAIMNU) Metro Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25217/numerical.v4i2.669

Abstract

Regional minimum wages might well represent the economic development of a region. The most likely spotlight province regarding the wage determination issue is East Java. This work is intended to obtain the best regression model on factors influencing East Java's regencies/cities' minimum wages in terms of spatial approach. The methods are Spatial Autoregressive (SAR) and Spatial Error Model (SEM). This study aims to obtain the best spatial model based on the factors influencing the regional minimum wage in districts/cities in East Java and the mapping. The data source is secondary data from Statistics Indonesia (BPS) of East Java. It consists of several variables, namely the Regional Minimum Wage, Total Working Population, Gross Regional Domestic Product, Total Population, and percentage of Population with a minimum education of senior high school. It shows that two significant factors are the number of working civilians and the percentage of high school-college graduates, affecting regional minimum wages. It proves that minimum wages among regions in East Java are spatially correlated with a closed area. Spatial regressions are the better ones than classic ones since they have higher R-sq and satisfy assumptions. Meanwhile, the selected model is SAR rather than SEM as it has a smaller AIC and explains variation better in minimum regional wages. It is indicated that some regions need more care due to small regional wages.
Spatial Regression Models on Factors Influencing Regional Minimum Wages Muhammad Luthfi Setiarno Putera
Numerical: Jurnal Matematika dan Pendidikan Matematika Vol. 4 No. 2 (2020)
Publisher : Institut Agama Islam Ma'arif NU (IAIMNU) Metro Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25217/numerical.v4i2.669

Abstract

Regional minimum wages might well represent the economic development of a region. The most likely spotlight province regarding the wage determination issue is East Java. This work is intended to obtain the best regression model on factors influencing East Java's regencies/cities' minimum wages in terms of spatial approach. The methods are Spatial Autoregressive (SAR) and Spatial Error Model (SEM). This study aims to obtain the best spatial model based on the factors influencing the regional minimum wage in districts/cities in East Java and the mapping. The data source is secondary data from Statistics Indonesia (BPS) of East Java. It consists of several variables, namely the Regional Minimum Wage, Total Working Population, Gross Regional Domestic Product, Total Population, and percentage of Population with a minimum education of senior high school. It shows that two significant factors are the number of working civilians and the percentage of high school-college graduates, affecting regional minimum wages. It proves that minimum wages among regions in East Java are spatially correlated with a closed area. Spatial regressions are the better ones than classic ones since they have higher R-sq and satisfy assumptions. Meanwhile, the selected model is SAR rather than SEM as it has a smaller AIC and explains variation better in minimum regional wages. It is indicated that some regions need more care due to small regional wages.
Co-Authors Setiarno Setiarno