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Analisis Faktor-Faktor yang Mempengaruhi Penyebaran Penyakit Demam Berdarah Dengue (Dbd) di Provinsi Jawa Tengah dengan Metode Spatial Autoregressive Model dan Spatial Durbin Model Arkadina Prismatika Noviandini Taryono; Dwi Ispriyanti; Alan Prahutama
Indonesian Journal of Applied Statistics Vol 1, No 1 (2018)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v1i1.24026

Dengue Hemorrhagic Fever is one of the major public health problems in Indonesia. From year to year, DHF causes Extraordinary Event in most parts of Indonesia, especially Central Java. Central Java consists of 35 districts or cities where each region is close to each other. Spatial regression is an analysis that suspects the influence of independent variables on the dependent variables with the influences of the region inside. In spatial regression modeling, there are spatial autoregressive model (SAR), spatial error model (SEM) and spatial autoregressive moving average (SARMA). Spatial durbin model is the development of SAR where the dependent and independent variable have spatial influence. In this research dependent variable used is number of DHF sufferers. The independent variables observed are population density, number of hospitals, residents and health centers, and mean years of schooling. From the multiple regression model test, the variables that significantly affect the spread of DHF disease are the population and mean years of schooling. Moran’s I test results stated that there are spatial dependencies between dependent and independent variables. The best model produced is the SAR model because it has the smallest AIC value of 49.61

ANALYSIS OF THE NUMBER INFANT AND MATERNAL MORTALITY IN CENTRAL JAVA INDONESIA USING SPATIAL-POISSON REGRESSION Alan Prahutama; Budi Warsito; Moch. Abdul Mukid
MEDIA STATISTIKA Vol 11, No 2 (2018): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Maternal and infant mortality are one of the most dangerous problems of the community since it can profoundly affect the number and composition of the population. Currently, the government has been taking heed on the attempt of reducing the number of maternal and newborn mortality in Central Java which requires data and information entirely. Poisson regression is a nonlinear regression that is often used to model the relationship between response variables in the form of discrete data with predictor variables in the form of discrete or continuous data. In space analysis, GWPR is one of method in space modeling which can model regional-based regression. It is based on some factors including the number of health facilities, the number of medical personnel, the percentage of deliveries performed with non-medical assistance; the average age of a woman's first marriage; the average education level of married women; average amount of per capita household expenditure; percentage of village status; the average rate of exclusive breastfeeding; percentage of households that have clean water and the percentage of poor people. Based on the analysis, it is revealed that the determinants of maternal and infant mortality in Central Java using Poisson and GWPR models, among others are the number of health facilities, the number of medical personnel, the average number of per capita household expenditure and the percentage of the poor. In the maternal and infant mortality model, the AIC value of GWPR model produces better modeling than Poisson regression. Keywords: Maternal and Infant mortality, Poisson, GWPR

MODELING CENTRAL JAVA INFLATION AND GRDP RATE USING SPLINE TRUNCATED BIRESPON REGRESSION AND BIRESPON LINEAR MODEL Suparti Suparti; Alan Prahutama; Agus Rusgiyono; Sudargo Sudargo
MEDIA STATISTIKA Vol 12, No 2 (2019): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Inflation and Gross Regional Domestic Income (GRDP) are two macroeconomic variables of a region that are correlated with each other. GRDP prices constant (real) can be used as an indicator of economic growth in a region from year to year. Inflation is calculated from the CPI rate and economic growth is calculated from the GRDP rate. Inflation and economic growth in an area are influenced by several factors including bank interest rates. Analysis of data consisting of 2 correlated responses can be performed with birespon regression analysis. In this research, modeling of inflation data and the rate of GRDP through birespon data modeling uses spline truncated nonparametric method and birespon linear parametric method. The purpose of this study is to model inflation data and the Central Java GRDP rate using spline truncated birespon regression. The results are compared with the birespon linear regression model. By using quarterly data from the first quarter of 2007 - the second quarter of 2019, the spline truncated model is better than the linear model, because the spline truncated model has a smaller MSE and R2 is greater than the linear model. Both models have the same performance which is quite good.

KLASIFIKASI KEMISKINAN DI KOTA SEMARANG MENGGUNAKAN ALGORITMA CHISQUARE AUTOMATIC INTERACTION DETECTION (CHAID) DAN CLASSIFICATION AND REGRESSION TREE (CART) Dwi Ispriyanti; Alan Prahutama; Mustafid Mustafid; Tarno Tarno
MEDIA STATISTIKA Vol 12, No 1 (2019): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Decreasing poverty level is the first goal of Sustainable Development Goals (SDGs). Poverty in Central Java from 2002 to 2017 has decreased, as well as the city of Semarang. Therefore, it is necessary to examine the factors that determine the decline in poverty classification in the city of Semarang. The classification analysis in statistics uses one classification tree. Several methods using classification trees include CART, CHAID, C45 and ID3 algorithms. In this study the methods used were CART and CHAID Algorithms. CART and CHAID algorithms are binary classification trees. The CART separation rules use split goodness op, while CHAID uses CHI-Square. In the analysis, the value of using CART was 95.2% while CHAID was 95.2%. While the factors that influence poverty classification using CHAID include the acceptance of poor rice, the main building materials of the house walls, and the main fuel for cooking. Whereas with the CART Algorithm the variables that influence are the main fuels for cooking, poor rice receipts, the number of household members, final disposal sites, sources of drinking water, the household head's business field, roofing materials, and building walls.

Pendampingan UKM Batik Bakaran dalam Upaya Peningkatan Produktivitas dan Kualitas Sugito Sugito; Alan Prahutama; Arief Rachman Hakim
Jurnal Surya Masyarakat Vol 5, No 1 (2022): November 2022
Publisher : Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsm.5.1.2022.26-33

The Covid-19 pandemic has greatly impacted the business sector, especially MSMEs (Micro, Small and Medium Enterprises). One of the government's efforts to overcome economic difficulties for affected MSME actors is capital assistance. In addition, MSMEs need assistance so that their managed businesses can run well in the midst of the COVID-19 pandemic. Diponegoro University through its community service program provides assistance to MSMEs. MSMEs that become partners are the SME Batik burned by Yuliati Warno and the SME Batik burned by Yahyu. Burnt batik is a typical batik of Pati district, Central Java. The method of implementing this activity is by analyzing the problems of SMEs through interviews and field observations. The program of activities carried out is based on the analysis of the problems that have been carried out. The program of activities includes aspects of production, aspects of licensing, aspects of marketing and aspects of human resources. Assistance is carried out by empowering SMEs including the use of appropriate technology, for example the use of feeders for the coloring and drying process, product diversification in the form of batik cloth masks. Licensing aspects include product standardization, such as the management of SIUP, registration of trademarks and processing of the "batik tulis Indonesia" batik mark. The marketing aspect is for example the use of digital marketing such as e-commerce platforms. The human resource aspect includes training on health protocols in the midst of the COVID-19 pandemic. This activity program is very helpful for SMEs Yuliati Warno and Yahyu in increasing their business.

Pendampingan UKM Batik Bakaran dalam Upaya Peningkatan Produktivitas dan Kualitas Sugito Sugito; Alan Prahutama; Arief Rachman Hakim
Jurnal Surya Masyarakat Vol 5, No 1 (2022): November 2022
Publisher : Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsm.5.1.2022.26-33

The Covid-19 pandemic has greatly impacted the business sector, especially MSMEs (Micro, Small and Medium Enterprises). One of the government's efforts to overcome economic difficulties for affected MSME actors is capital assistance. In addition, MSMEs need assistance so that their managed businesses can run well in the midst of the COVID-19 pandemic. Diponegoro University through its community service program provides assistance to MSMEs. MSMEs that become partners are the SME Batik burned by Yuliati Warno and the SME Batik burned by Yahyu. Burnt batik is a typical batik of Pati district, Central Java. The method of implementing this activity is by analyzing the problems of SMEs through interviews and field observations. The program of activities carried out is based on the analysis of the problems that have been carried out. The program of activities includes aspects of production, aspects of licensing, aspects of marketing and aspects of human resources. Assistance is carried out by empowering SMEs including the use of appropriate technology, for example the use of feeders for the coloring and drying process, product diversification in the form of batik cloth masks. Licensing aspects include product standardization, such as the management of SIUP, registration of trademarks and processing of the "batik tulis Indonesia" batik mark. The marketing aspect is for example the use of digital marketing such as e-commerce platforms. The human resource aspect includes training on health protocols in the midst of the COVID-19 pandemic. This activity program is very helpful for SMEs Yuliati Warno and Yahyu in increasing their business.

ANALISIS DISKRIMINAN BERGANDA DENGAN PEUBAH BEBAS CAMPURAN KATEGORIK DAN KONTINU PADA KLASIFIKASI INDEKS PRESTASI KUMULATIF MAHASISWA Nur Walidaini; Moch. Abdul Mukid; Alan Prahutama; Agus Rusgiyono
MEDIA STATISTIKA Vol 10, No 2 (2017): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Multiple discriminant analysis is one of the discriminant analysis techniques where the dependent variable are grouped into more than two groups. This paper discussed how to categorize Grade Point Average (GPA) of undergraduate student of Faculty of Sciences and Mathematics Diponegoro University based on categorical and continuous independent variable including gender, internet usage, time per week for learning, average score in national examination, amount of pocket money per month and the way to enter to Diponegoro University. The GPA grouping refers to the Academic Regulations of Diponegoro University i.e. satisfactory GPA (2,00 to 2,75), very satisfactory (2,76 to 3,50) and with honors (cum laude) (3,51 to 4,00). By using the multiple discriminant analysis with mixture variables, the accuration of classification based on training and testing data reach to 71,875% and 41,667% respectively.

Modelling Inflation Sectors in Indonesia Using Vector Autoregressive (VAR) Prahutama, Alan; Suparti, S.; Ispriyanti, Dwi; Utami, Tiani Wahyu
Jurnal ILMU DASAR Vol 20 No 1 (2019)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Analisis time series dapat dibagi menjadi dua yaitu analisis time series univariat dan analisis time series multivariat. Analisis time series univariat salah satunya menggunakan ARIMA, sedangkan analisis time series multivariat dapat menggunakan VAR. VAR merupakan pemodelan persamaan simultan yang memiliki beberapa variabel endogen secara bersamaan. Asumsi dalam model VAR antara lain terjadi kausalitas antar variabel (kausalitas Granger), residual white noise dan berdistribusi normal multivariat. Pada paper ini, metode VAR diimplementasikan dalam memodelkan sektor-sektor Inflasi di Indonesia. Adapun sektor-sektor tersebut antara lain sektor makanan (Y1t),Sektor Makanan Jadi, Minuman, Rokok dan Tembakau (Y2), Sektor perumahan, listrik, air, gas dan bahan bakar (Y3), Sektor Sandang (Y4), Sektor Kesehatan (Y5), Sektor Pendidikan dan Olahraga (Y6), Sektor Transportasi, Komunikasi dan Jasa Keuangan (Y7). Hasilnya adalah tidak semua variabel sektor inflasi berpengaruh terhadap sektor lainnya. Hanya beberapa variabel yang berpengaruh terhadap suatu sektor. Asumsi kausalitas Granger tidak semua dipenuhi oleh semua variabel. Begitu juga dengan normal multivariat juga tidak terpenuhi. Akan tetapi residual model sudah white noise. Keywords: vector autoregressive model, sectors of inflation, Granger Causality.

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