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Analisis Kemiskinan Menggunakan Model Panel Spasial Statik Jajang Jajang; Asep Saefuddin; I Wayan Mangku; Hermanto Siregar
MIMBAR (Jurnal Sosial dan Pembangunan) Volume 29, No. 2, Year 2013 [Accredited by Ristekdikti]
Publisher : Universitas Islam Bandung

The purpose of this research is to study the effects of GDP, population, employment of junior high school graduated, employment shares of agriculture, industry, trading and services to the number of poor people in Central Java Province. The method used to this modeling is spatial modeling. The results of research show that when GDP, employment shares of industry, trading and services are increase, the number of poor people is decrease. However, when the population, employment share of agriculture and employment of junior high school graduated are increase, the number of poor people is increase. Based on these findings there are some policies should be implemented to reduce the number of poor people, such as improvement of economic growth, improvement of education, controlling the population and employment transformation from agricultural sector to industry, trading and services sectors.

PEMODELAN FAKTOR-FAKTOR YANG MEMPENGARUHI KEMATIAN IBU MELAHIRKAN DI JAWA TENGAH DENGAN ZERO INFLATED POISSON REGRESSION Yusrina Ratna Annisa; Jajang Jajang; Agus Sugandha
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 12 No 2 (2020): Jurnal Ilmiah Matematika dan Pendidikan Matematika
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2020.12.2.3615

One of the targets of the Sustainable Development Goals (SDGs) is to reduce the maternal mortality rate by 2030. In reducing the maternal mortality rate, it is necessary to first study the factors that influence it. The number of maternal mortality rate in Central Java Province in 2018 was a discrete random variable that had a Poisson distribution and had many zero values. Generally, a model was used to counting data is Poisson regression model. However, the maternal mortality that has many zero values caused overdispersion. Therefore, Poisson model was not relevant in that case. In this paper, we used Zero Inflated Poisson (ZIP) model to overcome overdispersion caused by many zero values. The results of the research show that ZIP model can explained influence the number of maternal mortality. Based on this research, the factors such as provision of tablets, pregnant women who experience obstetric complications, and households with a clean and healthy lifestyle can explain the number of maternal mortality.

PEMODELAN KEBUTUHAN GIZI PADA BALITA DENGAN ARTIFICIAL NEURAL NETWORK jajang Jajang; Sylvia Meilani
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 13 No 1 (2021): Jurnal Ilmiah Matematika dan Pendidikan Matematika
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2021.13.1.4363

An information on the data is not easily obtained if the data is not presented well. The nutritional needs of toddlers are important to be studied to get an information about growth of these toddlers. This research studied the nutritional needs and its factors by using Artificial neural networks (ANN) model. These factors are toddler's age, gender, weight, height, activity. Nutrition data for children under five years old was obtained from interviews at 47 Posyandu locations. The results showed that the resulting ANN model gave quite good results where the error value generated was 0.024

ANALISIS REGRESI COUNT DATA UNTUK PEMODELAN JUMLAH KASUS PENYAKIT TUBERKULOSIS DI KABUPATEN BANYUMAS Kristy Kristy; Jajang Jajang; Nunung Nurhayati
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 13 No 2 (2021): Jurnal Ilmiah Matematika dan Pendidikan Matematika
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2021.13.2.4919

Tuberculosis is an infectious disease caused by Mycobacterium tuberculosis. Banyumas Regency is one of the districts with quite high Tuberculosis cases in Central Java. This study aims to analyze the factors that affect the number of tuberculosis cases in Banyumas Regency using regression analysis of count data. Poisson regression is the simplest count data regression model that has the assumption of equidispersion, that is, the mean value equal to the variance. However, in its application, these assumption is often not fulfilled, for example, there are cases of overdispersion (variance value is greater than the mean). In this study, to overcome the case of overdispersion, an approach was used using Generalized Poisson Regression (GPR) and negative binomial regression. The results showed that the data on the number of tuberculosis cases in Banyumas Regency in 2019 was overdispersion. The data modeling of the number of tuberculosis cases in Banyumas Regency with the negative binomial regression model is better than the GPR model. Meanwhile, the only predictor variable that affects the number of tuberculosis cases in Banyumas Regency is the sex ratio of productive age (15-49 years).

ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI KETIMPANGAN DISTRIBUSI PENDAPATAN DI PULAU JAWA TAHUN 2014-2020 Resta Dwi Andina; jajang Jajang; Supriyanto Supriyanto
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 13 No 1 (2021): Jurnal Ilmiah Matematika dan Pendidikan Matematika
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2021.13.1.4353

Unequal distribution of income is one indicator of community welfare. Improving and equalizing the standard of living people in various regions is one of the efforts to realize national economic development. The existence of an unequal distribution of income also has an impact on economic development. This study discusses panel data regression analysis to determine the factors that affect the unequal distribution of income in Java from 2014 to 2020 with the help of Eviews 10 software. The factors that are thought to affect unequal distribution of income in this study are the Human Development Index (HDI), Open Unemployment Rate (OPR), Regional Gross Domestic Product (RGDP) per capita, and total of poor people. The fixed effects model (FEM) was chosen to be the best model. The results showed that the HDI and RGDP per capita variables had negative and significant effect on unequal distribution of income in Java from 2014 to 2020.

ANALISIS FAKTOR-FAKTOR YANG BERPENGARUH TERHADAP KINERJA PEGAWAI PT. KERETA API INDONESIA (PERSERO) DAOP 5 PURWOKERTO DENGAN PARTIAL LEAST SQUARE Jajang Jajang; Supriyanto Supriyanto; Dimas Eka Putra
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 12 No 2 (2020): Jurnal Ilmiah Matematika dan Pendidikan Matematika
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2020.12.2.3613

In this research, PLS method is applied to analyze which factor are affect employee performance in PT. Kereta Api Indonesia (Persero) DAOP 5 Purwokerto based on variables that are research factors that is employee performance, work motivation, leadership, training, work enviroment and corporate culture through the indicator which are then analyzed. From analysis using a PLS method with 6 variables of research, it was found that R-square value work of motivation variables of 77,00% with good assessments defined by construct variable of leadership, training, work enviroment and corporate culture while another 23% is described by other variables outside this research. The value of R-square on employee performance variables of 66,00% with good enough assessment criteria described by the work of motivation, where as another 34% is described by other variables outside this research model.

POWER AND SIZE OF NORMAL DISTRIBUTION AND ITS APPLICATIONS Budi Pratikno; Jajang Jajang; Setianingsih Setianingsih; Raden Sudarwo
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 9 No 2 (2017): Jurnal Ilmiah Matematika dan Pendidikan Matematika
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2017.9.2.2871

. The research studied power and size of normal distribution and its applications on linear regression model. The power and size formulas are derived, and the unrestricted test (UT), restrcited test (RT) and pre-test test (PTT) are used. The recommendation of the test is given by choosing maximum power and minimum size, and also graphical analysis. The result showed that the power and size for large standard deviation () tend to be identical and flat. In simulation study, the graphs of the UT, RT, and PTT are still similar to the previous research (Pratikno, 2012), where the PTT tend to lie between UT and RT.

IMPLEMENTASI MODEL REGRESI LOGISTIK MULTINOMIAL PADA PENGELOMPOKAN PENYAKIT TUBERKULOSIS Mella Apriyani; jajang Jajang; Agustini Tripena Br. Sb.
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 13 No 1 (2021): Jurnal Ilmiah Matematika dan Pendidikan Matematika
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2021.13.1.3612

There are three types of Tuberculosis (TB) patients at Banyumas Region Hospital, namely negative pulmonary TB, positive pulmonary TB, and extra pulmonary TB. Types of TB generally caused by age, cae of history, gender, level of education, and domicile. One of the methods that used to find a correlation between types of TB with the affect is regression analysis. This study used multinomial logistic regession analysis because types of TB is categorical and the data is 156 TB’s patients recorded at 2018/2019. The result showed that the level of education be a dominant factor to affect TB. Here, we noted that patients with basic education level have a 5,843 time odds for getting positive pulmonary TB and 2,224 times for getting extra pulmonary TB. The multinomial logistic regression model is then given as probability for getting positive pulmonary TB with factor level of education is greather than negative pulmonary TB and extra pulmonary TB.

POWER AND SIZE OF NORMAL DISTRIBUTION AND ITS APPLICATIONS Budi Pratikno; Jajang Jajang; Setianingsih Setianingsih; Raden Sudarwo
Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Vol 9 No 2 (2017): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2017.9.2.2871

. The research studied power and size of normal distribution and its applications on linear regression model. The power and size formulas are derived, and the unrestricted test (UT), restrcited test (RT) and pre-test test (PTT) are used. The recommendation of the test is given by choosing maximum power and minimum size, and also graphical analysis. The result showed that the power and size for large standard deviation () tend to be identical and flat. In simulation study, the graphs of the UT, RT, and PTT are still similar to the previous research (Pratikno, 2012), where the PTT tend to lie between UT and RT.

IMPLEMENTASI MODEL REGRESI LOGISTIK MULTINOMIAL PADA PENGELOMPOKAN PENYAKIT TUBERKULOSIS Mella Apriyani; jajang Jajang; Agustini Tripena Br. Sb.
Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Vol 13 No 1 (2021): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2021.13.1.3612

There are three types of Tuberculosis (TB) patients at Banyumas Region Hospital, namely negative pulmonary TB, positive pulmonary TB, and extra pulmonary TB. Types of TB generally caused by age, cae of history, gender, level of education, and domicile. One of the methods that used to find a correlation between types of TB with the affect is regression analysis. This study used multinomial logistic regession analysis because types of TB is categorical and the data is 156 TB’s patients recorded at 2018/2019. The result showed that the level of education be a dominant factor to affect TB. Here, we noted that patients with basic education level have a 5,843 time odds for getting positive pulmonary TB and 2,224 times for getting extra pulmonary TB. The multinomial logistic regression model is then given as probability for getting positive pulmonary TB with factor level of education is greather than negative pulmonary TB and extra pulmonary TB.

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