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PEMODELAN KASUS DIARE DI PROVINSI BALI DENGAN METODE ANALISIS REGRESI SPASIAL
I.G.A. DIAH SULASIH;
MADE SUSILAWATI;
NI LUH PUTU SUCIPTAWATI
E-Jurnal Matematika Vol 10 No 2 (2021)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
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DOI: 10.24843/MTK.2021.v10.i02.p327
Diarrhea is a disease that occurs due to changes in the frequency of bowel movements and can cause death. In 2018, 115.889 cases of diarrhea were found in Bali Province. Information on the relationship between locations indicates the spatial effect in the model. Model estimation was done by using spatial regression analysis. This study aims to determine what factors influence diarrhea cases in Bali Province. The results show that the number of diarrhea cases in a district is influenced by the surrounding districts. This is reinforced in the Moran’s I test which shows spatial dependence. In the analysis of the Spatial Error Model (SEM), it was obtained that the value of was 57,69% and the variables that significantly affected diarrhea cases in Bali Province were population density and sanitation facilities
PENGEMBANGAN PROGRAM BERITA INFOTAINMENT TV NASIONAL BERDASARKAN PREFERENSI MASYARAKAT MENGGUNAKAN ANALISIS KONJOIN
PUTRI DAMEYANTI;
MADE SUSILAWATI;
DESAK PUTU EKA NILAKUSMAWATI
E-Jurnal Matematika Vol 9 No 4 (2020)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
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DOI: 10.24843/MTK.2020.v09.i04.p308
Current technological advances cause information to be obtained quickly. Such information can be obtained through printed media or electronic media. Television is included in the category of electronic media. The infotainment program is one of the television programs. Almost all television stations have infotainment programs running every day. This proves that people love the infotainment program, so the infotainment program still running until now. People’s as watchers/audiens of the infotainment program have the right to provide an assessment of the quality of infotainment programs related to satisfaction and preference to assist in the development of infotainment programs. To understand people's preferences for infotainment programs, it can be done using conjoint analysis. In this research, it was found that the attributes that influence the people’s in watching infotainment program are presenter, air time, and program duration. In general, the infotainment program that desired by the people was an infotainment program that has a paired presenter, running at night with a half hour run time
PEMODELAN JUMLAH KASUS PENYAKIT KUSTA DI PROVINSI JAWA TIMUR
NI MADE SUKMA PERTIWI;
I KOMANG GDE SUKARSA;
MADE SUSILAWATI
E-Jurnal Matematika Vol 9 No 1 (2020)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
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DOI: 10.24843/MTK.2020.v09.i01.p277
Spatial Autoregressive Model (SAR) is a combination of linear regression models with spatial lag in response variables that consider spatial effects. One problem that considers spatial effects is leprosy cases. This study aims to predict the number of leprosy cases models in East Java Province and the factors that influence it. The type of data used in this study is secondary data obtained from the publication of the Health Profile of East Java Province in 2017 and the publication of the Central Statistics Agency (CSA) of East Java Province. The results of this study indicate that the SAR model can describe the number of leprosy cases in East Java Province with AIC value is 109,951 and value is 71,93%. The factors that influence the number of leprosy cases are the percentage of healthy houses and the number of health centers in each district/city in East Java Province.
PEMODELAN PENYEBARAN KASUS DEMAM BERDARAH DENGUE (DBD) DI KOTA DENPASAR DENGAN METODE SPATIAL AUTOREGRESSIVE (SAR)
NI MADE SURYA JAYANTI;
I WAYAN SUMARJAYA;
MADE SUSILAWATI
E-Jurnal Matematika Vol 6 No 1 (2017)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
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DOI: 10.24843/MTK.2017.v06.i01.p146
One of spatial regression model is Spatial Autoregressive (SAR), which assumes that the autoregressive process only on the dependent variable only by considering the spatial effects. There are two aspects of spatial effects, that is spatial dependence and spatial heterogeneity. One of the problems which considers spatial effect is the spread of Dengue Hemorrhagic Fever (DHF). Denpasar City is an endemic DHF disease because there have been DHF cases in three consecutive years or more. The purpose of this research is to estimate the spread of DHF in Denpasar City along with the factors that affect it. The results show that the factors that influence the spread of DHF are neighborhood, area and the role of Jumantik at the every village in Denpasar City.
PEMODELAN KASUS PNEUMONIA PADA BALITA DI PROVINSI BALI MENGGUNAKAN METODE REGRESI NONPARAMETRIK B-SPLINE
I GUSTI AYU MADE VALENTINA DEWI;
I GUSTI AYU MADE SRINADI;
MADE SUSILAWATI
E-Jurnal Matematika Vol 9 No 3 (2020)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
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DOI: 10.24843/MTK.2020.v09.i03.p299
Pneumonia is an inflammatory lung disease caused by bacterium Streptococcus pneumonia, Chlamydophila pneumonia bacteria, influenza virus, and fungi. Bali Provincial Health Service data in 2018 shows that one of the diseases that causes many deaths in children under five is pneumonia. This study aims to model the number of pneumonia cases in children under five in Bali Province in 2018 with six research variables, namely percentage of low birth weight, percentage of coverage of infants who receive vitamin A, percentage of infants who receive exclusive breastfeeding, percentage of under-five health services, percentage of villages that implement community-based total sanitation, and percentage of neonatal complications management. In the B-Spline function there are connecting points called knots. The best estimation of the B-Spline regression model is obtained from selecting the optimum knot point with the criteria for the value of generalized cross validation (GCV) and the selected mean square error (MSE) having the minimum value. The B-Spline regression model that is formed is the quadratic B-Spline model (order 3) with five knots resulting in an value of 87.79%.
ANALISIS REGRESI NONPARAMETRIK SPLINE MULTIVARIAT UNTUK PEMODELAN INDIKATOR KEMISKINAN DI INDONESIA
DESAK AYU WIRI ASTITI;
I WAYAN SUMARJAYA;
MADE SUSILAWATI
E-Jurnal Matematika Vol 5 No 3 (2016)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
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DOI: 10.24843/MTK.2016.v05.i03.p129
The aim of this study is to obtain statistics models which explain the relationship between variables that influence the poverty indicators in Indonesia using multivariate spline nonparametric regression method. Spline is a nonparametric regression estimation method that is automatically search for its estimation wherever the data pattern move and thus resulting in model which fitted the data. This study, uses data from survey of Social Economy National (Susenas) and survey of Employment National (Sakernas) of 2013 from the publication of the Central Bureau of Statistics (BPS). This study yields two models which are the best model from two used response variables. The criterion uses to select the best model is the minimum Generalized Cross Validation (GCV). The best spline model obtained is cubic spline model with five optimal knots.
IMPLEMENTASI ANALISIS FAKTOR DALAM MENGANALISIS KEPUASAN NASABAH TERHADAP KUALITAS LAYANAN (STUDI KASUS: LPD SIDAKARYA)
I PUTU ARISTA YASA;
NI LUH PUTU SUCIPTAWATI;
MADE SUSILAWATI
E-Jurnal Matematika Vol 6 No 2 (2017)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
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DOI: 10.24843/MTK.2017.v06.i02.p160
The aim of this study was to be able to determine some factors that affected customer satisfaction on the quality of the services provided by LPD Sidakarya. Samples of this study were 150 respondents. The respondents were customers of LPD Sidakarya who have been registered since at least a year ago. There were two variables in this study; i.e. perception and expectation variables in which each of the variable had 30 indicators that affected the satisfaction of the customer on service quality. In addition, this study also determined five factors that affected customer satisfaction on the service quality. The method used was confirmatory factor analysis. It was found on the results of this study that the formed factor of these 30 indicators that affected the satisfaction of the customer on service quality indeed five main factors consisted of tangibles, reliability, responsiveness, assurance and empathy. The most dominant factor obtained was reliability.
PENERAPAN METODE NEWEY WEST DALAM MENGOREKSI STANDARD ERROR KETIKA TERJADI HETEROSKEDASTISITAS DAN AUTOKORELASI PADA ANALISIS REGRESI
ZAKIAH NURLAILA;
MADE SUSILAWATI;
DESAK PUTU EKA NILAKUSMAWATI
E-Jurnal Matematika Vol 6 No 1 (2017)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
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DOI: 10.24843/MTK.2017.v06.i01.p142
Ordinary Least Squares (OLS) used to estimate the parameters in the regression analysis. If one of the assumptions is not fulfilled, the results of the OLS are no longer best, linear, and unbiased properties. The aim of this research was to find out the application of Newey West method to correct standard error when heteroscedasticity and autocorrelation occurred, and to compare the results of OLS with Newey West method on secondary and simulation data. OLS can still be used to estimate the regression parameter when heteroscedasticity and autocorrelation occurred. However, it will cause bias on standard error of parameter. A method which can correct the standard error of parameters to be unbiased parameter is Newey West method. The secondary data about Passenger Car Milage and data simulated contain heteroscedasticity and autocorrelation. The analysis showed that the Newey West method were known is able to correct standard error when heteroscedasticity and autocorrelation occurred on both of data. It was obtained that Newey west method with and changes the value of the bias standard error of OLS to be unbiased.
ANALISIS WAKTU KELULUSAN MAHASISWA DENGAN METODE CHAID (STUDI KASUS: FMIPA UNIVERSITAS UDAYANA)
IDA AYU SRI PADMINI;
LUH PUTU SUCIPTAWATI;
MADE SUSILAWATI
E-Jurnal Matematika Volume 1, No 1, Tahun 2012
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
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DOI: 10.24843/MTK.2012.v01.i01.p016
This research aim to knowing the variables classification that distinguish graduated time student between proper time with not proper time on FMIPA Udayana Universities with use CHAID Method. This research conducted at FMIPA Udayana Universities, with research sample about 751 persons student graduated FMIPA Udayana Universities period February 2008 until August 2011. CHAID method produce 7 segment there are: student graduated from Biology department and Chemistry women gender; from Biology and Chemistry man gender; from Mathematic department and Physic with IPK?3,00; from Mathematic department and Physic with IPK>3,00 and thesis period?6 months; from Mathematic department and Physic with IPK>3,00 and period thesis>6 months; from Pharmacy as well as student graduated from Computer science department.
PENDUGAAN DATA HILANG DENGAN METODE YATES DAN ALGORITMA EM PADA RANCANGAN LATTICE SEIMBANG
MADE SUSILAWATI;
KARTIKA SARI
E-Jurnal Matematika Vol 4 No 2 (2015)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
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DOI: 10.24843/MTK.2015.v04.i02.p092
Missing data often occur in agriculture and animal husbandry experiment. The missing data in experimental design makes the information that we get less complete. In this research, the missing data was estimated with Yates method and Expectation Maximization (EM) algorithm. The basic concept of the Yates method is to minimize sum square error (JKG), meanwhile the basic concept of the EM algorithm is to maximize the likelihood function. This research applied Balanced Lattice Design with 9 treatments, 4 replications and 3 group of each repetition. Missing data estimation results showed that the Yates method was better used for two of missing data in the position on a treatment, a column and random, meanwhile the EM algorithm was better used to estimate one of missing data and two of missing data in the position of a group and a replication. The comparison of the result JKG of ANOVA showed that JKG of incomplete data larger than JKG of incomplete data that has been added with estimator of data. This suggest thatwe need to estimate the missing data.