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Media Statistika

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Published by Universitas Diponegoro

ISSN : - EISSN : 24770647 DOI : -

Core Subject : Science,

Decision Sciences, Operations Research & Management

Arjuna Subject : -

Articles 6 Documents

Search results for , issue "Vol 10, No 1 (2017): Media Statistika" : 6 Documents clear

Klasifikasi Data Berat Bayi Lahir Menggunakan Weighted Probabilistic Neural Network (WPNN) (Studi Kasus di Rumah Sakit Islam Sultan Agung Semarang) Yasin, Hasbi; Ispriyansti, Dwi
MEDIA STATISTIKA Vol 10, No 1 (2017): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Low Birthweight (LBW) is one of the causes of infant mortality. Birthweight is the weight of babies who weighed within one hour after birth. Low birthweight has been defined by the World Health Organization (WHO) as weight at birth of less than 2,500 grams (5.5 pounds). There are several factors that influence the BWI such as maternal age, length of gestation, body weight, height, blood pressure, hemoglobin and parity. This study uses a Weighted Probabilistic Neural Network (WPNN) to classify the birthweight in RSI Sultan Agung Semarang based on these factors. The results showed that the birthweight classification using WPNN models have a very high accuracy. This is shown by the model accuracy of 98.75% using the training data and 94.44% using the testing data.Keywords:Birthweight, Classification, LBW, WPNN.

Perbandingan Model Estimasi Artificial Neural Network Optimasi Genetic Algorithm dan Regresi Linier Berganda Sebayang, Jimmy Saputra; Yuniarto, Budi
MEDIA STATISTIKA Vol 10, No 1 (2017): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Multiple Linear Regression is a statistical approach most commonly used in performing predictive data modeling. One of the methods that can be used in estimating the parameters of the model on Multiple Linear Regression is Ordinary Least Square. It has classical assumptions requirements and often the assumptions are not satisfied. Another method that can be used as an alternative data modeling is Artificial Neural Network. It is Â a free-distribution estimator because there's no assumptions that have to be satisfied.Â However, modeling data using ANN has some problems such as selection of network topology, learning parameters and weight initialization. Genetic Algorithm method can be used to solve those problems. A set of simulation data was generated to test the reliability of ANN-GA model compared to Multiple Linear Regression model. Model comparison experiments indicate that ANN-GA model are better than Multiple Linear Regression model for estimating simulation data both on the data training and data testing.Keywords:Neural Network, Genetic Algorithm, Ordinary Least Square

Perbandingan Sensitivitas Harga Obligasi Berdasarkan Durasi Macaulay dan Durasi Eksponensial dengan Pengaruh Konveksitas (Studi Empiris pada Data Obligasi Korporasi Indonesia yang Terbit Tahun 2015) Maruddani, Di Asih I; Hoyyi, Abdul
MEDIA STATISTIKA Vol 10, No 1 (2017): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Macaulay duration has often been used as a measure of the bond prices sensitivity to changes in interest rates. For a small change in interest rates, the duration provides a good approximation of the actual change in price. As the change in interest rates gets larger, the duration approximation has larger errors. The convexity of bond prices change is often used as a way to improve the accuracy of the approximation. Several authors have pointed out that the natural logarithm of bond price is a better measure of percentage changes in bond prices as interest rates change. Based on this idea, this paper derives an accurate method of estimating percentage bond price changes in response to changes in interest rates, which is called exponential duration. This paper gives new estimation of bond prices using exponential duration with convexity approach. It will be shown that the new estimation bond prices is always more accurate than by Macaulay duration with convexity approach. For empirical study, it is used corporate bond data, which is published by Indonesian Bond Pricing Agency in 2015. The result support the theory that error value of Macaulay duration with convexity is more than the error value of exponential duration with convexity.Keywords:Bond Price, Convexity, Exponential Duration, Macaulay Duration, Modified Duration

Penerapan Regresi Logistik Ordinal Proportional Odds Model pada Analisis Faktor-Faktor yang Mempengaruhi Kelengkapan Imunisasi Dasar Anak Balita di Provinsi Aceh Tahun 2015 Budyanra, Budyanra; Azzahra, Ghaida Nasria
MEDIA STATISTIKA Vol 10, No 1 (2017): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Province of Aceh has basic immunization coverage toddler lowest in Indonesia in 2015. even though, this province has Posyandu and Puskesmas ratio per population of the highest in the western region of Indonesia. This data their concerns regarding immunization coverage has not been handled well in Aceh Province. This papers aims to identify variables that affect the status of complete basic immunization of children aged 12-59 months in Aceh by using ordinal logistic regression analysis. Ordinal logistic regression model used is proportional odds models. Data are obtained from Susenas 2015 that was held in March 2015 by BPS-Statistic of Indonesia. Based on the results of processing data, known only 37.7% of children aged 12-59 months in the province of Aceh in 2015 which gets fully immunized, the remaining 50.6% receive primary immunization but is not complete, even about 11.7% have not received basic immunization at all. From the proportional odds model results showed that the number of children born to mothers (odds ratio = 0.88), maternal age at delivery (odds ratio = 1.03), the level of maternal education (odds ratio = 1.22), and the educational level of the household (odds ratio = 1,2) have a significant impact on the status of complete basic immunization of children. Future studies are expected to include the element of timeliness and add other variables and also with other models in ordinal logistic regression.Keywords:Immunization, Ordinal Logistic Regression, Proportional Odds, Susenas

Metode Nonlinear Least Square (NLS) untuk Estimasi Parameter Model Wavelet Radial Basis Neural Network (WRBNN) Santoso, Rukun; Sudarno, Sudarno
MEDIA STATISTIKA Vol 10, No 1 (2017): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The use of wavelet radial basis model for forecasting nonlinear time series is introduced in this paper. The model is generated by artificial neural network approximation under restriction that the activation function on the hidden layers is radial basis. The current model is developed from the multiresolution autoregressives (MAR) model, with addition of radial basis function in the hidden layers. The power of model is compared to the other nonlinear model existed before, such as MAR model and Generalized Autoregressives Conditional Heteroscedastic (GARCH) model. The simulation data which be generated from GARCH process is applied to support the aim of research. The sufficiency of model is measured by sum squared of error (SSE). The computation results show that the proposed model has a power as good as GARCH model to carry on the heteroscedastic process.Keywords:Wavelet, Radial Basis, Heteroscedastic Model, Neural Network Model.

Rancangan D-Optimal Model Gompertz dengan Maple Widiharih, Tatik; Warsito, Budi
MEDIA STATISTIKA Vol 10, No 1 (2017): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Gompertz model is used in many areas including biological growth studies, animal and husbandry, chemistry, and agricultural. Locally D-optimal designs for Gompertz models with three parameters is investigated. We used the Generalized Equivalence Theorem of Kiefer and Wolvowitz to determine D-optimality criteria. Tchebysheff system is used to decide that the D-optimal design is minimally supported design or nonminimally supported design. The result, D-optimal design for Gompertz model is minimally supported design with uniform weight on its support.Keywords:D-optimal, Generalized Equivalence Theorem, Tchebysheff System,Â Minimally Supported, Uniform Weight.

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